HDFS-17299. Adding rack failure tolerance when creating a new file

Description of PR
Adding rack failure tolerance when creating a new file. During create file operation(see logs in jira), in case of bad rack, the create operation failed and hence the operation was not rack failure tolerant. This was not same as what happens during append phase where min replication factor is applicable.
Adding this update to fix this behavior to make the create phase on the lines of append phase.
How was this patch tested?
Added Test Cases for following scenarios:-

testSingleRackFailureDuringPipelineSetup_MinReplicationPossible (Min replication allows some DNs in pipeline to be stopped)
testSingleRackFailureDuringPipelineSetup_MinReplicationImpossible (Min replication doesn't allow some DNs in pipeline to be stopped)
testMultipleRackFailureDuringPipelineSetup_MinReplicationPossible  (Stopping DNs on multiple racks and still min replication allows some DNs in pipeline to be stopped)
testMultipleRackFailureDuringPipelineSetup_MinReplicationImpossible(Stopping DNs on multiple racks and min replication doesn't allow DNs in pipeline to be stopped)
testAllRackFailureDuringPipelineSetup(Stopping all DNs which should not allow creating a file)

For code changes:

[X] Does the title or this PR starts with the corresponding JIRA issue id (e.g. 'HADOOP-17799. Your PR title ...')?
[ ] Object storage: have the integration tests been executed and the endpoint declared according to the connector-specific documentation?
[ ] If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?
[ ] If applicable, have you updated the LICENSE, LICENSE-binary, NOTICE-binary files?

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Reason
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Failed junit tests
hadoop.hdfs.protocol.datatransfer.sasl.TestSaslDataTransfer

hadoop.hdfs.TestAbandonBlock

hadoop.hdfs.server.namenode.TestDiskspaceQuotaUpdate

hadoop.hdfs.server.sps.TestExternalStoragePolicySatisfier

hadoop.hdfs.server.blockmanagement.TestBlockStatsMXBean

hadoop.hdfs.server.datanode.fsdataset.impl.TestDatanodeRestart

hadoop.hdfs.server.datanode.TestDataNodeMetrics

hadoop.hdfs.TestBlocksScheduledCounter

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureToleration

hadoop.hdfs.TestFileAppend

hadoop.hdfs.TestDFSClientExcludedNodes

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureReporting

hadoop.hdfs.server.namenode.ha.TestPipelinesFailover

hadoop.hdfs.server.datanode.TestDiskError

hadoop.hdfs.server.datanode.fsdataset.impl.TestSpaceReservation

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hadoop.hdfs.server.datanode.TestDirectoryScanner

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448m 54s

Reason
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Failed junit tests
hadoop.hdfs.server.datanode.TestDirectoryScanner

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Reason
Tests

Failed junit tests
hadoop.hdfs.TestFileChecksum

hadoop.hdfs.TestBlocksScheduledCounter

hadoop.hdfs.server.datanode.fsdataset.impl.TestSpaceReservation

hadoop.hdfs.protocol.datatransfer.sasl.TestSaslDataTransfer

hadoop.hdfs.server.datanode.TestDirectoryScanner

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureToleration

hadoop.hdfs.TestDatanodeDeath

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureReporting

hadoop.hdfs.server.datanode.TestDiskError

hadoop.hdfs.TestDFSClientExcludedNodes

hadoop.hdfs.TestDFSStripedInputStream

hadoop.hdfs.server.namenode.ha.TestPipelinesFailover

hadoop.hdfs.TestDecommissionWithStriped

hadoop.hdfs.server.sps.TestExternalStoragePolicySatisfier

hadoop.hdfs.server.namenode.metrics.TestNameNodeMetrics

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailure

hadoop.hdfs.server.datanode.TestDataNodeMetrics

hadoop.hdfs.TestAbandonBlock

hadoop.hdfs.server.namenode.TestNamenodeRetryCache

hadoop.hdfs.server.namenode.TestDiskspaceQuotaUpdate

hadoop.hdfs.TestFileAppend

Subsystem
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GITHUB PR
https://github.com/apache/hadoop/pull/6513

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux 5b33cc284e50 5.15.0-88-generic #98-Ubuntu SMP Mon Oct 2 15:18:56 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux

Build tool
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Personality
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git revision
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test4tests
0m  0s

The patch appears to include 3 new or modified test files.

_ trunk Compile Tests _

+0 :ok:
mvndep
14m  6s

Maven dependency ordering for branch

+1 :green_heart:
mvninstall
22m  8s

trunk passed

+1 :green_heart:
compile
3m 16s

trunk passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
compile
2m 51s

trunk passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
checkstyle
0m 42s

trunk passed

+1 :green_heart:
mvnsite
1m  8s

trunk passed

+1 :green_heart:
javadoc
1m  1s

trunk passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javadoc
1m 27s

trunk passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
spotbugs
3m  0s

trunk passed

+1 :green_heart:
shadedclient
23m 21s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 51s

Maven dependency ordering for patch

+1 :green_heart:
mvninstall
1m  8s

the patch passed

+1 :green_heart:
compile
3m 17s

the patch passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javac
3m 17s

the patch passed

+1 :green_heart:
compile
2m 54s

the patch passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
javac
2m 54s

the patch passed

+1 :green_heart:
blanks
0m  0s

The patch has no blanks issues.

-0 :warning:
checkstyle
0m 39s
/results-checkstyle-hadoop-hdfs-project.txt
hadoop-hdfs-project: The patch generated 16 new + 243 unchanged - 2 fixed = 259 total (was 245)

+1 :green_heart:
mvnsite
1m  1s

the patch passed

+1 :green_heart:
javadoc
0m 50s

the patch passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javadoc
1m 21s

the patch passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
spotbugs
3m 10s

the patch passed

+1 :green_heart:
shadedclient
23m 37s

patch has no errors when building and testing our client artifacts.

_ Other Tests _

+1 :green_heart:
unit
1m 45s

hadoop-hdfs-client in the patch passed.

-1 :x:
unit
204m 31s
/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt
hadoop-hdfs in the patch passed.

+1 :green_heart:
asflicense
0m 27s

The patch does not generate ASF License warnings.

319m 54s

Reason
Tests

Failed junit tests
hadoop.hdfs.server.namenode.TestAuditLogs

hadoop.hdfs.TestBlocksScheduledCounter

hadoop.hdfs.server.datanode.fsdataset.impl.TestSpaceReservation

hadoop.hdfs.protocol.datatransfer.sasl.TestSaslDataTransfer

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureToleration

hadoop.hdfs.TestDatanodeDeath

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureReporting

hadoop.hdfs.server.datanode.TestDiskError

hadoop.hdfs.TestGetBlocks

hadoop.hdfs.TestDFSClientExcludedNodes

hadoop.hdfs.server.namenode.ha.TestPipelinesFailover

hadoop.hdfs.server.sps.TestExternalStoragePolicySatisfier

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailure

hadoop.hdfs.TestReconstructStripedFileWithValidator

hadoop.hdfs.server.datanode.TestDataNodeMetrics

hadoop.hdfs.TestAbandonBlock

hadoop.hdfs.server.namenode.TestNamenodeRetryCache

hadoop.hdfs.server.namenode.TestDiskspaceQuotaUpdate

hadoop.hdfs.TestErasureCodingPolicies

hadoop.hdfs.TestFileAppend

Subsystem
Report/Notes

Docker
ClientAPI=1.44 ServerAPI=1.44 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/7/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/6513

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux d164b58dc0d3 5.15.0-88-generic #98-Ubuntu SMP Mon Oct 2 15:18:56 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / 98d287ebd902f0639703d23d648ee90765b14f88

Default Java
Private Build-1.8.0_392-8u392-ga-1~20.04-b08

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_392-8u392-ga-1~20.04-b08

Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/7/testReport/

Max. process+thread count
4140 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs-client hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/7/console

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@ritegarg  There are still 45 test faiures in the latest run. Please take a look.

@ayushtkn  @Hexiaoqiao Can you guys please provide some early feedback? Thank you.

Overall the changes looks good. @ritegarg Can you please add a comment on why you changed the signature of setupPipelineForAppendOrRecovery method.

Updated

@ritegarg There are still 45 test faiures in the latest run. Please take a look.

Fixed locally, started a new Jenkins build

:confetti_ball: +1 overall

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0m  0s

detect-secrets was not available.

+1 :green_heart:
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0m  0s

The patch does not contain any @author tags.

+1 :green_heart:
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0m  0s

The patch appears to include 3 new or modified test files.

_ trunk Compile Tests _

+0 :ok:
mvndep
14m 22s

Maven dependency ordering for branch

+1 :green_heart:
mvninstall
35m 28s

trunk passed

+1 :green_heart:
compile
6m  6s

trunk passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
compile
5m 55s

trunk passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
checkstyle
1m 31s

trunk passed

+1 :green_heart:
mvnsite
2m 21s

trunk passed

+1 :green_heart:
javadoc
1m 54s

trunk passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javadoc
2m 17s

trunk passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
spotbugs
5m 55s

trunk passed

+1 :green_heart:
shadedclient
40m  3s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 31s

Maven dependency ordering for patch

+1 :green_heart:
mvninstall
2m  1s

the patch passed

+1 :green_heart:
compile
5m 55s

the patch passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javac
5m 55s

the patch passed

+1 :green_heart:
compile
5m 36s

the patch passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
javac
5m 36s

the patch passed

+1 :green_heart:
blanks
0m  1s

The patch has no blanks issues.

-0 :warning:
checkstyle
1m 18s
/results-checkstyle-hadoop-hdfs-project.txt
hadoop-hdfs-project: The patch generated 16 new + 243 unchanged - 2 fixed = 259 total (was 245)

+1 :green_heart:
mvnsite
2m  3s

the patch passed

+1 :green_heart:
javadoc
1m 32s

the patch passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javadoc
2m  0s

the patch passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
spotbugs
6m  1s

the patch passed

+1 :green_heart:
shadedclient
39m 53s

patch has no errors when building and testing our client artifacts.

_ Other Tests _

+1 :green_heart:
unit
2m 24s

hadoop-hdfs-client in the patch passed.

+1 :green_heart:
unit
258m  1s

hadoop-hdfs in the patch passed.

+1 :green_heart:
asflicense
0m 48s

The patch does not generate ASF License warnings.

445m 39s

Subsystem
Report/Notes

Docker
ClientAPI=1.44 ServerAPI=1.44 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/8/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/6513

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux a59f38e0e351 5.15.0-88-generic #98-Ubuntu SMP Mon Oct 2 15:18:56 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / 04db2288b0964d44c7a918bc1324f95ee376f51b

Default Java
Private Build-1.8.0_392-8u392-ga-1~20.04-b08

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_392-8u392-ga-1~20.04-b08

Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/8/testReport/

Max. process+thread count
2842 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs-client hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/8/console

versions
git=2.25.1 maven=3.6.3 spotbugs=4.2.2

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:broken_heart: -1 overall

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Docker mode activated.

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+1 :green_heart:
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0m  0s

No case conflicting files found.

+0 :ok:
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0m  1s

codespell was not available.

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detsecrets
0m  1s

detect-secrets was not available.

+1 :green_heart:
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0m  0s

The patch does not contain any @author tags.

+1 :green_heart:
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0m  0s

The patch appears to include 3 new or modified test files.

_ trunk Compile Tests _

+0 :ok:
mvndep
14m 46s

Maven dependency ordering for branch

+1 :green_heart:
mvninstall
35m  1s

trunk passed

+1 :green_heart:
compile
6m 12s

trunk passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
compile
5m 48s

trunk passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
checkstyle
1m 28s

trunk passed

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mvnsite
2m 19s

trunk passed

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javadoc
1m 53s

trunk passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javadoc
2m 19s

trunk passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
spotbugs
6m  1s

trunk passed

+1 :green_heart:
shadedclient
40m 13s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+0 :ok:
mvndep
1m  2s

Maven dependency ordering for patch

+1 :green_heart:
mvninstall
1m 59s

the patch passed

+1 :green_heart:
compile
6m  0s

the patch passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javac
6m  0s

the patch passed

+1 :green_heart:
compile
5m 37s

the patch passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
javac
5m 37s

the patch passed

+1 :green_heart:
blanks
0m  0s

The patch has no blanks issues.

-0 :warning:
checkstyle
1m 21s
/results-checkstyle-hadoop-hdfs-project.txt
hadoop-hdfs-project: The patch generated 16 new + 243 unchanged - 2 fixed = 259 total (was 245)

+1 :green_heart:
mvnsite
2m  3s

the patch passed

+1 :green_heart:
javadoc
1m 33s

the patch passed with JDK Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04

+1 :green_heart:
javadoc
2m  7s

the patch passed with JDK Private Build-1.8.0_392-8u392-ga-1~20.04-b08

+1 :green_heart:
spotbugs
6m  5s

the patch passed

+1 :green_heart:
shadedclient
39m 42s

patch has no errors when building and testing our client artifacts.

_ Other Tests _

+1 :green_heart:
unit
2m 25s

hadoop-hdfs-client in the patch passed.

-1 :x:
unit
257m 45s
/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt
hadoop-hdfs in the patch passed.

+1 :green_heart:
asflicense
0m 43s

The patch does not generate ASF License warnings.

446m  4s

Reason
Tests

Failed junit tests
hadoop.hdfs.server.namenode.TestDiskspaceQuotaUpdate

hadoop.hdfs.server.sps.TestExternalStoragePolicySatisfier

hadoop.hdfs.TestDFSClientExcludedNodes

hadoop.hdfs.server.namenode.ha.TestPipelinesFailover

Subsystem
Report/Notes

Docker
ClientAPI=1.44 ServerAPI=1.44 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/9/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/6513

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux 41aa593ac88e 5.15.0-88-generic #98-Ubuntu SMP Mon Oct 2 15:18:56 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / 3a24ff0393874c3ce44928c8fe94a0ee6ed3ddeb

Default Java
Private Build-1.8.0_392-8u392-ga-1~20.04-b08

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.21+9-post-Ubuntu-0ubuntu120.04 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_392-8u392-ga-1~20.04-b08

Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/9/testReport/

Max. process+thread count
2825 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs-client hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6513/9/console

versions
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Closing this PR in favor of https://github.com/apache/hadoop/pull/6556/files


Add SimpleString::npos & use as default amount in subString()

Coverage remained the same at 99.873% when pulling 8c746e355bf2fe8a5c99bb9487efbbadc9c408a4 on arstrube:npos into 40bcde7d5cf89c9667467d1fc7e2a64020ebe2b5 on cpputest:master.

Coverage remained the same at 99.873% when pulling 736378b6157426fa4fb5a9c470e64ecc31b28692 on arstrube:npos into 40bcde7d5cf89c9667467d1fc7e2a64020ebe2b5 on cpputest:master.

Coverage remained the same at 99.873% when pulling 453037f97c97e9f8115572a9030fa796fbbc3420 on arstrube:npos into 40bcde7d5cf89c9667467d1fc7e2a64020ebe2b5 on cpputest:master.

Coverage remained the same at 99.873% when pulling 453037f97c97e9f8115572a9030fa796fbbc3420 on arstrube:npos into 40bcde7d5cf89c9667467d1fc7e2a64020ebe2b5 on cpputest:master.

Can we override the SubString with just one parameter instead, so we don't need the public npos static variable?

Public npos is gleaned from Standard C++. I find it rather useful (that was the whole point). Have a look at the next PR and let's then decide.
It needn't be public, of course, but I do find it usefu.....

From www.cplusplus.com:
public static member constant
std::string::npos
static const size_t npos = -1;
Maximum value for size_t
npos is a static member constant value with the greatest possible value for an element of type size_t.
This value, when used as the value for a len (or sublen) parameter in string's member functions, means "until the end of the string".
As a return value, it is usually used to indicate no matches.
This constant is defined with a value of -1, which because size_t is an unsigned integral type, it is the largest possible representable value for this type.

If you absolutely don't want npos, then we could use size() as default argument and still have a more convenient subString(), but when I raised the issue, I was really missing SimpleString::npos. I'd consider the default argument to subString rather as a nice-to-have.

Coverage remained the same at 99.873% when pulling 712a4aea66673afef83dad11d1df0b89409a4403 on arstrube:npos into c92072393011f596cd3dcd003e5388520c36f87b on cpputest:master.

Coverage remained the same at 99.874% when pulling 553bcdef6067b74808335424158d53d73d522d6d on arstrube:npos into 7ea6f14e2e984d03d4911c65402b30bedc1fd487 on cpputest:master.

This can be closed now, right?

yes


gethlslink endpoint not working properly

Hello
Not related to php sdk it seems, but related to API itself.
$pCloudFolder = new pCloud\Sdk\Folder($pCloudApp);   $content = $pCloudFolder->getContent($_GET['folderId']);   $request = new pCloud\Sdk\Request($pCloudApp);   foreach ($content as $item) {          if (strpos($item->name, 'm3u8') !== false) {              	$response = $request->get("gethlslink", ['fileid' => $item->fileid]); // this produces error              	//$response = $request->get("getfilelink", ['fileid' => $item->fileid]); // this is ok           }    }
When I try to API directly from the terminal :
// works perfectly
curl -X GET
'https://eapi.pcloud.com/getfilelink?fileid=123456&access_token=thisisascret'
// gives 1000 error (log in required, but the access token works for previous curl command)
curl -X GET
'https://eapi.pcloud.com/gethlslink?fileid=123456&access_token=thisisascret'
According to the documentation, both endpoints should require exactly the same input parameters so I don't understand...

Just a heads up.
https://docs.pcloud.com/methods/streaming/gethlslink.html
You using eapi (Europe), in the documentation is listed as only api.pcloud.com.


_InternalLinkedHashMap has no instance method 'foreach'

Full runtime error:
NoSuchMethodError: Class '_InternalLinkedHashMap<String, dynamic>' has no instance method 'foreach'.
jsonDecode is giving me a _InternalLinkedHashMap which doesn't have a foreach implementation like Map.  It is confusing and an annoyance not to have these types have compatible interfaces.
reproduction:
final Map<String, dynamic> data =
    jsonDecode(content) as Map<String, dynamic>;
data['results'].foreach((k, v) { print('$k $v'); });

where content is:
{
  "results": {
    "foo": 1,
    "bar": 2,
  }
}

This is my error.  'Map' and '_InternalLinkedHashMap' both implement 'forEach', not 'foreach'.


Network stack has memory leak

When benchmarking nginx performance, it failed with oom.

Solved by dynamically expanding kernel heap.


fix(chat): add 'today', 'pinned conversations', 'pinned prompts' and 'recent' sections expansion if create new chat/folder/prompt (Issue #1552)

Description:
add 'today', 'pinned conversations', 'pinned prompts' and 'recent' sections expansion if create new chat/folder/prompt
Issues:

Issue #1552

Checklist:

[x] the pull request name complies with Conventional Commits
[x] the pull request name starts with fix(<scope>):, feat(<scope>):, feature(<scope>):, chore(<scope>):, hotfix(<scope>): or e2e(<scope>):. If contains breaking changes then the pull request name must start with fix(<scope>)!:, feat(<scope>)!:, feature(<scope>)!:, chore(<scope>)!:, hotfix(<scope>)!: or e2e(<scope>)!: where <scope> is name of affected project: chat, chat-e2e, overlay, shared, sandbox-overlay, etc.
[x] the pull request name ends with (Issue #<TICKET_ID>) (comma-separated list of issues)
[x] I confirm that do not share any confidential information like API keys or any other secrets and private URLs

/deploy-review


 Recent advancements in quantum computing have opened new pathways for solving differential equations with greater efficiency. The paper Hamiltonian Simulation for Hyperbolic Partial Differential Equations by Scalable Quantum Circuits by Yuki Sato et al. proposes a method for solving certain partial differential equations by transforming them into a Schrödinger equation, which can then be solved via Hamiltonian simulation on a quantum computer.
Project Overview
Challenge: Implement the technique outlined in the referenced paper to solve the advection equation with Dirichlet boundary conditions. You will test both a Hamiltonian simulation method of your choice and the circuit implementation proposed in the paper.
Objective
Solve the following advection equation with Dirichlet boundaries:
$$ \frac{d\psi}{dt} = \frac{d\psi}{dx} = 0$ $$
$$
\psi(0, x) =
\begin{cases}
1, & \text{if } 1 < x < 2 \
0, & \text{otherwise}
\end{cases}
$$

Implement a parametrized quantum program as a function of time.
Run a single execution of the quantum algorithm using the statevector simulator for $t = 1.0$.
Compare CX-gate counts between the paper’s proposed quantum circuit and a Hamiltonian simulation using Classiq for different time values.

Deliverables

Jupyter Notebook containing:

A quantum program implemented in Classiq to execute the algorithm.
A graphical visualization of the resulting function $\psi(x, t=1.0)$.
A quantitative analysis of CX-gate counts for both the quantum circuit from the paper and the Hamiltonian simulation via Classiq, presented in a graphical format.

Follow the Contribution Guidelines in CONTRIBUTING.md. If you need any assistance, feel free to reach out via GitHub or join our Slack Community.
Getting Started

Review Paper: Study the method described in Hamiltonian Simulation for Hyperbolic Partial Differential Equations by Scalable Quantum Circuits by Yuki Sato et al.
Set Up Environment: Create a new Jupyter Notebook and install the Classiq SDK; refer to the setup guide.
Guiding Materials:

Classiq 101 - Introduction to platform concepts.
Classiq Fundamentals Workshop - Hands-on Classiq basics.
Platform walkthrough on home page.

Implementation Steps

Algorithm Coding:

Implement the algorithm for solving the advection equation with Classiq SDK.
Define the Hamiltonian based on the advection equation and parameterize it as a function of time.
Document steps in markdown, following the Glued Trees Example.
For support, contact us on GitHub or Slack.

Mathematical Explanation:

Use markdown and LaTeX to explain theoretical background, key equations, and algorithm insights.

Generate .qmod File:

Use write_qmod(model, "filename.qmod") to save your models.
Confirm successful notebook execution and .qmod file generation.

Quality Check:

Proofread for accuracy and ensure code correctness.
Use clear markdown formatting and a professional presentation.

Submit Contribution:

Follow Contribution Guidelines.
Open a Pull Request in classiq-library/research/differential_equation_simulation.
Include a summary of insights and results.

Resources

Reference Paper: Hamiltonian Simulation for Hyperbolic Partial Differential Equations by Scalable Quantum Circuits by Yuki Sato et al.
Classiq Documentation: Classiq Library
Glued Trees Example: Link
Contribution Guidelines: CONTRIBUTING.md

Note: No strict deadline. Confirm with us if you start this task so we can assign it to you.
Good Luck!

Hey, I have successfully implemented the algorithm yesterday, but for some reason I have the error '’module ‘pydantic’ has no attribute ‘model_validator' showing up, without updating or changing any packages. May I ask how to resolve this? Thanks!

I think I have implemented the algo in the paper. Would it be possible to have a check with someone from classiq? Thanks.

Hi @AprilSweettooth
It seems that someone just asked that in the community (maybe you? :) ). Here is the link to the answer:
pydantic

Hi. model_validator exists in pydantic since version 2, and since version 0.52 classiq depends on version 2 of pydantic.
From the error it seems like the environment you have classiq installed in also has pydantic 1.
You can try upgrading your classiq SDK by running pip install -U classiq and it should update the pydantic dependency as well.
If you have a different package installed that needs pydantic 1 you should either check if there is a version of that package that supports pydantic 2, or use a virtual environment to separate the package with conflicting dependencies.

Let us know if you want to take this issue @AprilSweettooth

Hi @AprilSweettooth It seems that someone just asked that in the community (maybe you? :) ). Here is the link to the answer: pydantic

Hi. model_validator exists in pydantic since version 2, and since version 0.52 classiq depends on version 2 of pydantic.
From the error it seems like the environment you have classiq installed in also has pydantic 1.
You can try upgrading your classiq SDK by running pip install -U classiq and it should update the pydantic dependency as well.
If you have a different package installed that needs pydantic 1 you should either check if there is a version of that package that supports pydantic 2, or use a virtual environment to separate the package with conflicting dependencies.

Yes, this is resolved now, thanks!

Let us know if you want to take this issue @AprilSweettooth

Yes, please.

Hello @AprilSweettooth!
Do you plan to open a PR on this issue?

Hi @NadavClassiq, sorry I haven't found time to write up the explanation yet!

Hi @AprilSweettooth, that is perfectly fine.
I just want to know if I should be assigned to this task and possibly know when to expect a PR, not restrictively.

Hi @NadavClassiq, if that's the case, please feel free to make any necessary adjustments to the assignment, as I don’t want to hold up the progress of the task.


Feasibility of instantiating homomorphic encryption as SNARK circuit

Could someone give some opinions on the feasibility of instantiating a circuit for performing homomorphic function eval with known (encrypted) inputs as a SNARK?
That's because some of us from this world want some computational integrity guarantees in the multiparty setting when doing delegated, privacy-preserving computing.
The reason we would want homomorphic encryption is that we would like to obscure inputs from the server (prover) performing the computations. For this reason, there is not really a strong requirement for zero-knowledge, since all inputs could be considered public, since they are encrypted anyway (although in practice it may be better to keep them private to leak less information, in case a private key gets leaked, for instance). However, there may be parts of our schemes such as encryption and decryption that could possibly be worth verifying for a multiparty protocol.
We have deterministic circuits (no recursion and can unroll loops deterministically), operations involving modular arithmetic wrt prime moduli, number theoretic transform, data permutations. It is unclear that many of the optimisations seen in current implementations (SEAL, Lattigo, Palisade) such as RNS word size decompositions would be the right choices for a SNARK circuit.
I would assume we would want some efficiency during setup, since we are passing different inputs to the same circuit, but each output given inputs must be verified independently. We would also prefer not to encounter any toxic waste. I have to think further about whether proof sizes are an issue by comparing it with average data transmission size per atomic circuit.
Which of the available schemes might be best for our purposes?

Sorry, didn't get around to responding to this sooner. Closing this for now, feel free to comment if you'd still like to continue a discussion.
Most of the various (non-recursive) SNARKs right now can be thought of as mainly varying in two parameters, one is the intermediate representation they take as input, and the second is the cryptographic compiler they use to get a SNARK. (What compiler has the fastest prover for a given representation keeps on changing, the trust assumptions it requires don't)
The roughly 5 compilers you have are (and the works that explicitly use it):

Transparent Setup, Post-Quantum - Fractal, AIR-STARK, Aurora, Ligero.
Transparent DL based, linear verifier - Bulletproofs.
Transparent Class group vector commitment based -  SuperSonics.
Trusted Universal Setup - Marlin, Plonk, Sonic.
Circuit specific trusted setup (This only supports R1CS) - Groth16, GM17. These are the fastest provers for R1CS atm.

Given that you want no toxic waste and not post-quantumness, then if you can tolerate linear verifiers, BulletProofs (slash anything obtained using that compiler) should be the fastest for your purpose.
I don't know your circuit well enough to know which of the two common intermediate representations (AIR / R1CS) would be better. However for almost all common circuits with repeated sub-structure that I'm aware of being interesitng, AIR provers outperform R1CS ones if you spend enough time optimizing the AIR constraint system.


Opt-in regional S3 buckets.

Continuation of #456. This is being reopened to resolve a coverage issue
Part of the SigV2 -> SigV4 saga. This is necessary to facilitate SigV4 regional buckets. Initially, it'll create more buckets per test (1 per region), but those buckets will be retained (emptied if necessary).
New buckets will be auto-created in this format:
taskcat-<account_id_hash>-<region_name>.
Note: No modifications to $[taskcat_autobucket] are necessary due to the current design
Special things to consider:

This is opt-in via s3_regional_buckets from global down to test-level.
Please pay special attention to these functions:

Dataclasses:

generate_bucket_name,
- generate_regional_bucket_name,

Config:

_create_regional_bucket_obj
_create_legacy_bucket_obj

/do-e2e-tests

end to end tests failed

botocore.exceptions.ClientError: An error occurred (BucketNotEmpty) when calling the DeleteBucket operation: The bucket you tried to delete is not empty

/do-e2e-tests

Building codebuild image...
getting temporary credentials...
executing e2e test container... (privileged mode needed for docker in docker)
running tests using 3.7.4...
running tests in help.sh...
running tests in lint.sh...
running tests in package.sh...
running tests in test.sh...
running tests using 3.6.9...
running tests in help.sh...
running tests in lint.sh...
running tests in package.sh...
running tests in test.sh...
ALL TESTS PASSED

/do-e2e-tests


LoadError: cannot load such file -- neo4j/tasks/neo4j_server.rake

Obsolete wiki.
The content of the Rakefile should be:
load 'neo4j/rake_tasks/neo4j_server.rake'

Thanks for finding this!  I think I might have fixed this from somebody else's report.  Was this the wiki page/section?
https://github.com/neo4jrb/neo4j-core/wiki#usage-from-neo4j-server

Yes it is in the "Usage from Neo4j Server" section.

Oh, weird, I thought I had fixed it, but it looks like it wasn't fixed.  Fixed now, thanks so much!


cargo clippy fails on NixOS

When I run cargo clippy on a project which has llama as a dependency, I get the following odd error, which doesn't happen on cargo build (both after cargo clean):
error: failed to run custom build command for `llama v0.11.1`

Caused by:
  process didn't exit successfully: `/home/daniel/code/nail/target/debug/build/llama-746d7d6fa29797c5/build-script-build` (exit status: 101)
  --- stderr
  thread 'main' panicked at 'called `Result::unwrap()` on an `Err` value: Os { code: 13, kind: PermissionDenied, message: "Permission denied" }', /home/daniel/.local/share/cargo/registry/src/github.com-1ecc6299db9ec823/llama-0.11.1/build.rs:31:36
  note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace

Looking at the source for build.rs, it looks like there's a workaround for getting it to work on docs.rs: https://github.com/zshipko/llama/blob/master/build.rs#L4-L5
Could we add the same for clippy? i.e. (disclaimer: untested),
#[cfg(feature = "cargo-clippy")]
fn main() {}

#[cfg(not(any(feature = "docs-rs", feature = "cargo-clippy")))]
fn main() {
// ...
}

~BTW, is the build script really necessary? I don't remember inkwell having one (and I'd imagine that all the necessary work is already done by llvm-sys, no?).~ Nevermind that.

Turns out this is specific to NixOS.


[VueJS] Add Pinia into Vue generator + generated

We could add an API to add Pinia which replaces VueX for state management into a Vue app

Besides it's usefull for ticket #897

@seraphinandrieux : which are the recommandations from Vue core team about this subject?

Ok here the answer: https://vuejs.org/guide/scaling-up/state-management.html

Yep :)
Could you assign this ticket to me ?


[QST] Why were TPC Benchmarks Removed?

Recently the TPC benchmarks were removed from the project repository. Why were the benchmarks and results removed? Are there any major modifications that were made to the tpc(like) benchmarks that were in this repo compared to official benchmark query templates or a framework like this one from databricks?

Hi @barnes88, thanks for the question.  We are still using industry standard benchmarks for this project.  We felt it best to keep the benchmarks outside of the repository for the time being and are considering where best to host them.  We did not make any major modifications compared to the queries that are in the databricks repository.


IJ Plugin UI strings refer to internal name Blaze instead of OSS name Bazel

A few placed in the IJ plugin still display "Blaze" rather than "Bazel".
Example:

This has been resolved in https://github.com/bazelbuild/intellij/commit/9aa67de97d01abaeb7fd051579fd3a7d49b16c6e, will be available in the next plugin release.


Powercalc-Measure support for arm64 (Raspberry pi)

Checklist

[X] I have filled out the template to the best of my ability.
[X] This only contains 1 feature request (if you have multiple feature requests, open one feature request for each feature request).
[X] This issue is not a duplicate feature request of previous feature requests.

Is your feature request related to a problem? Please describe.
This addon is for Home Assistant.
Home Assistant is most used on a RaspberryPi
Contributing to power-calc requires to run a docker container image.
Such docker ocntainer is only available in linux/amd64
As a result it can't be run within the home-assistant most used hardware.
Describe the solution you'd like
Docker measure support for arm64 which is Raspberry pi latest' platform.
Describe alternatives you've considered
Running python on another computer and messing up with dependencies, environments, and discrepancies which is just too much.
Additional context
Because HA already exposes ways to create Addons (which are HA-compatible docker containers), this could potentially help to do such migration to a HA-addonn-baseline image so that it runs in all supported HA platforms.
Nice to have: measure reelased as an HA addon (with environment variables defined through addon config) would greatly help on getting more calculations done from more users.
Thanks!

I have also build an image for arm64 now.
See https://hub.docker.com/layers/bramgerritsen/powercalc-measure/feat-multi-platform/images/sha256-5dab6d6314a4032119a7f1f5e384cb43f4b1eb1a9952c14f1b570f1ff8091428?context=explore.
Are you able to test this and verify it's working. Before I merge to master.
HA addon is not really an option, as it not really allows for interactive prompts.
Did have a look into that in the past.

Haven't had the chance yet sorry. I'll try in 1-2 weeks.

Ok thanks. Closing this issue. When it is not working when you test we can reopen.


Do not delete finalizer until the probe returns status not ready

This PR fixes a problem that we have since we were deleting the
finalizer without deleting the topic accordingly since we were
return nil in FinalizeKind which deletes the finalizer from
the resource.
Signed-off-by: Pierangelo Di Pilato<EMAIL_ADDRESS>Fixes #1798

/cherry-pick release-1.1

/cherry-pick release-1.2

/retest

panic: test timed out after 1h0m0s

/retest

/test pull-knative-sandbox-eventing-kafka-broker-upgrade-tests

/retest

/unhold

/retest

/assign @matzew @aliok


GO:0044796 DNA polymerase processivity factor complex?

GO:0044796 DNA polymerase processivity factor complex
A protein complex which is capable of increasing the processivity of nucleotide polymerization by DNA polymerase as a part of DNA replication.
This is an odd complex term. Its a grouping term, but its only grouping  complexes based on the fact that these are doing similar processes (not even that similar because PCNA does lots of things). Seems  bit arbitrary?

Hi Val,
Actually, it's just the complex that is capable of GO:0030337 DNA polymerase processivity factor activity.
The complex term was requested by me for the beta clamp of the E.coli replication machinery but the MF is much older.
See:
http://www.ebi.ac.uk/intact/complex/details/EBI-6468862
If you search the CP for the GO:0044796 it will also bring up all of our PCNA complexes.
Birgit

Ah ok


HHH-11871 - during metamodel generation, verify if methods respect JavaBeans conventions

When the JPAMetaModelEntityProcessor is executed, a new AnnotationMetaEntity is created for each Entity.
When the AnnotationMetaEntity is created, for a specific entity (Java class), each member of the class was registered as a persistent member. In this pull request, only members of class that respects the JavaBeans convention are added as persistent members.
I was thinking about this fix, by reading the Java API specification : "If the entity uses persistent properties, the entity must follow the method conventions of JavaBeans components.".
The same specification describes the metamodel generation : "For each entity class in a particular package, a metamodel class is created with a trailing underscore and with attributes that correspond to the persistent fields or properties of the entity class."

Thank you! But I think you try to fix this at the wrong place.
Your method "methodRespectsJavaBeansConvention()" is redundant, because this is already checked at /util/StringUtil.isProperty(String methodName, String returnTypeAsString). This method is called by /annotation/MetaAttributeGenerationVisitor.visitExecutable(ExecutableType t, Element p), which is (indirectly) called by /annotation/AnnotationMetaEntity.addPersistentMembers(List<? extends Element> membersOfClass, AccessType membersKind).
I think the additional check for the method parameters (one for setters, none for getters) should be done in MetaAttributeGenerationVisitor.visitExecutable(...) or in AnnotationMetaEntity.addPersistentMembers(...), whichever is more convinient.

Hi!
Than you for the observations. I will, first, explain why I added the check in that place. Then, some additional thoughts I had based on your suggestion.
I have added the check in that place, because the method call addPersistentMembers( methodsOfClass, AccessType.PROPERTY ); adds the methods in the members map (please see members.put( result.getPropertyName(), result ); ). The example Homework class (from tests) has, among others, in this order, 2 methods: public List<String> getPaths(), public Set<String> getPaths(String startPath). If both methods are added to the map, the second method overwrites the first one. This is why, issue can be reproduced when the 2 methods are listed in this order: public List<String> getPaths(), public Set<String> getPaths(String startPath); by reversing the order of declaration, issue is no longer reproducible, because the good method overwrites the bad one in the map.
Based on your suggestion, I tried to replace the newly added method methodRespectsJavaBeansConvention() with /util/StringUtil.isProperty(String methodName, String returnTypeAsString), thus eliminating duplicate code. But the method /util/StringUtil.isProperty does not check if method has parameter, thus both List<String> getPaths() and Set<String> getPaths(String startPath) would pass the check.
However, your suggestion made me think, maybe Boolean properties can start both with 'is' and 'has'.
According to JPA specification and this document, boolean getter may start with 'is'. Further suggestions are welcome.

This PR targets 5.1 branch.
Closing this PR, to add a new one targeting the master branch.


Travis build is failing

The new travis build succeeded a few times, but now it's failing with some kind of message about package corruption (files missing from the text package).

@peterbecich  Any ideas?

/home/travis/build/google/codeworld/codeworld-api/src/CodeWorld/CanvasM.hs:25:1: error:
    Could not find module ‘Data.Text’
    There are files missing in the ‘text-<IP_ADDRESS>’ package,
    try running 'ghc-pkg check'.
    Use -v to see a list of the files searched for.
   |
25 | import Data.Text (Text)
   | ^^^^^^^^^^^^^^^^^^^^^^^

That problem went away, but now we've got a timeout running travis_apt_get_update.  This seems to be very flaky, and I don't know what to do about it.

Seems to be okay for now.

@cdsmith please delete all the Travis caches, I'm guessing here https://travis-ci.org/google/codeworld/caches

@peterbecich Done


[Blocker] The plugin UI comes out as a blank white window

Hello,
I have been using the add-on for a while without any problem but today (after a week without using it), the UI comes out as a blank white window.

Firefox version
42.0a2

The problem is that some of the image files you used for layers have been removed from the disk. It generated exceptions and the popup wasn't properly initialized.
(one optional fix is to remove the data.json file from your Firefox profile directory. It's under pixel-perfect dir)
Please keep your data file as is and use the new patched version (see the link below). Layers with missing images on the local hard drive should be automatically removed from the list. Use the new version and let me know if it works for you.
http://janodvarko.cz/temp/pixel-perfect/pixelperfectplugin-2.0.7-issue.68.xpi
The patch fixes also thumbnails in the layer-list (not properly displayed in Fx42).
Thanks!
Honza

Sorry, I just removed the data.json file while reading the second paragraph. It works now, I will reproduce it again by deleting an used file.

Thanks, I want to release new version and I need someone to verify the fix.
Honza

The white screen issues is fixed but now the images are not properly loaded. I tried with different images/pages. See the broken image at the left of the UI.

Are you still running Firefox 42?
Honza

Yes, same environment.

Hm..., I can't reproduce the problem on my machine
Can you try to create a  new fresh Firefox profile and run only PixelPerfect in it?
https://getfirebug.com/wiki/index.php/Install_Firebug_into_a_clean_profile
Can you send me the image (perhaps there could be a problem with the format?)
Honza

It works correctly with a fresh profile in both Firefox 40 and 42. :+1:

Do you have another extension (in your original profile) installed that could cause a collision?
Or do you have any tips about what could cause the problem?
Honza

I've disabled all the extensions and it did work but after enable all of them, it still works. Quite strange. Tried to reproduce it again and it works.

I see, ok.
Anyway, I am closing this report and I am also going to release a new version with the patch for this report included.
Feel free to make another report if you'd experience any problem.
Thanks for the help!
Honza

Great. Thanks for the support!


[Feature] Add HTTP Sink Connector

Search before asking

[X] I had searched in the issues and found no similar issues.

Feature Request
Send CloudEvents to a specific URL of a HTTP server (like a SpringBoot application endpoint or more).
Are you willing to submit PR?

[ ] Yes I am willing to submit a PR!

Code of Conduct

[X] I agree to follow this project's Code of Conduct *

Is completing the above TODO part? I think I can give it a try. Please assign it to me. Thanks~~

@Pil0tXia
I've used OkHttpClient to build an HTTP Sink Connector.
I have some questions regarding message acknowledgment:
I currently check the HTTP response status code and whether the response body is empty to ensure message delivery success. Should we establish a response template specifying the expected response codes and messages to confirm whether messages were successfully processed, or to retrieve information about the reasons for processing failure?
Do you have any recommendations on this?

@cnzakii
I think an HTTP 200 response is enough to represent that the receiver processed the message correctly.
EventMesh is planning in the future to have statistics on the delivery status of events, when it will be necessary to show the results of Webhook deliveries, including what is returned on the sink side. You may leave an extensible design with comments.
Could you please use vertx which has been used in the HTTP Source Connector? Using the same third-party library improves code reusability and later extensibility, and avoids the problem that the Source Connector may produce faster than the Sink Connector can consume.

@Pil0tXia
OK, I will make the modifications based on your suggestions.

@Pil0tXia
I have a dependency issue to resolve in the eventmesh-connector-http module. The version io.cloudevents:cloudevents-http-vertx:2.3.0 uses Vert.x version 4.0.0, conflicting with io.vertx:vertx-web:4.4.6, causing issues with vertx.WebClient functionality.
My current approach is:

Upgrading io.cloudevents:cloudevents-http-vertx from 2.3.0 to 3.0.0.
Downgrading io.vertx:vertx-web from 4.4.6 to 4.3.7.

This is because the latest version of io.cloudevents:cloudevents-http-vertx available is 3.0.0, which uses Vert.x version 4.3.7.

@cnzakii
This is the current version in master branch:
https://github.com/apache/eventmesh/blob/fe2bd7c840c9900ad7143099d89a1cc1905a9a09/eventmesh-connectors/eventmesh-connector-http/build.gradle#L21-L22

The version io.cloudevents:cloudevents-http-vertx:2.3.0 uses Vert.x version 4.0.0, conflicting with io.vertx:vertx-web:4.4.6

For the same artifact, Gradle automatically uses the latest version in the dependency tree. If the old version is completely unupgradeable (which is important because upgrading a version is almost always better than downgrading), you can exclude transitive dependencies from conflicting artifacts.
When upgrading, read the release note to avoid unintentionally breaking the functionality of the original code.
My understanding of the situation you described is this:

While the existing io.vertx:vertx-web:4.4.6 and io.cloudevents:cloudevents-http-vertx:2.3.0 work well with the HTTP Source Connector, the WebClient class where HTTP Sink Connector required to introduce does not work with this version.
In order for the WebClient to work properly, io.cloudevents:cloudevents-http-vertx:2.3.0 needs to be upgraded to io.cloudevents:cloudevents-http-vertx:3.0.0.
io.clouddevents:clouddevents-http-vertx:3.0.0 and the existing io.vertx:vertx-web:4.4.6 still do not allow WebClient to work properly, and io.vertx:vertx-web:4.4.6 must be downgraded to io.vertx:vertx-web:4.3.7 (is this step correct? For most artifacts, higher versions are backwards compatible)

@Fungx May I ask that what do you think of @cnzakii 's dependency conflict?

@Pil0tXia
Simply upgrading io.cloudevents:cloudevents-http-vertx from version 2.3.0 to 3.0.0 allows the unit tests for the HttpSourceConnector to run successfully. However, it doesn't guarantee the absence of other potential conflicts.

@cnzakii

Therefore, we have two solutions:

Please do both. I've read the release notes of https://github.com/cloudevents/sdk-java, and it seems that there's no breaking change related to vertx between 2.3.0 and 3.0.0.
According to https://vertx.io/docs/vertx-web-client/java/#_using_the_web_client, developers should declare their dependencies explicitly. I think the latest version won't have compatibility issues either.

@Pil0tXia  PTAL


retrive saved error during training in Python?

It is related to #1274, so I want to plot the training and validation metrics, and I have used
mx.callback.log_train_metric(5) which works. I am just wondering to which variable is it saved and how do I load it after training? Or could I save it directly to some file during training? Thanks a lot!

figured it out!


istiod helm chart: add affinity and tolerations

Describe the feature request
Currently, we can set "nodeSelector" on the istiod helm chart, but we cannot add tolerations.
=> in our system, the "cluster" nodes have taints, and we'd like to have istiod to run on those system nodes.
Describe alternatives you've considered
Affected product area (please put an X in all that apply)
[ ] Docs
[X] Installation
[ ] Networking
[ ] Performance and Scalability
[ ] Extensions and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure
Affected features (please put an X in all that apply)
[ ] Multi Cluster
[ ] Virtual Machine
[ ] Multi Control Plane
Additional context

did you still working on https://github.com/istio/istio/pull/38318?

No: looks like it's more complicated than I thought :/ So I closed it and hope that someone can do it properly.

/assign zirain

ok, I'll take a look at this later.

@jgournet I think https://github.com/istio/istio/pull/37513 added those, anything I missed?

@zirain :
https://github.com/istio/istio/pull/37513 did add affinity and tolerations into the deployment file, but did not add them in the values.yaml file, making them not usable (as far as I know ?)
I then tried to add them into the values.yaml file in my PR, but tests started failing - that's where I stopped


SB5 incompatible with create-react-app?

Describe the bug
This is with create-react-app, with the latest version of react-scripts (2.1.8) and SB (5.0.2).  Works fine locally but when deployed I get an error about conflicting webpack versions.  Node modules, package-lock deleted etc.
Code snippets
Heres the error:
`react-scripts build
There might be a problem with the project dependency tree.
It is likely not a bug in Create React App, but something you need to fix locally.
The react-scripts package provided by Create React App requires a dependency:
"webpack": "4.28.3"
Don't try to install it manually: your package manager does it automatically.
However, a different version of webpack was detected higher up in the tree:
/var/lib/jenkins/workspace/project/project-Deploy/node_modules/webpack (version: 4.29.6)
`

Works for me.
Installation:
npx create-react-app cra-latest
cd cra-latest/
npx -p @storybook/cli sb init

Storybook side:
yarn storybook
yarn build-storybook
serve -s storybook-static

CRA side:
yarn start
yarn build
serve -s build

@shilman is there a way to avoid using yarn? company doesn't want to have two package managers :\

@jacobgranberry I expect if I follow the same steps with the npm equivalent commands it will have the same results. Have not verified:
npm run storybook
npm run build-storybook
serve -s storybook-static

npm start
npm run build
serve -s build

Possibly better related to https://github.com/storybooks/storybook/issues/5935 and https://github.com/storybooks/storybook/issues/6081, but running the exact same commands on a fresh install results in performance issues:
yarn build-storybook
yarn run v1.10.1
$ build-storybook -s public
info @storybook/react v5.0.3
info
info clean outputDir..
info => Copying static files from: public
info => Copying prebuild dll's..
info => Building manager..
info => Loading manager config..
info => Loading presets
info => Loading custom addons config.
info => Compiling manager..

WARNING: We noticed you're using the `useBuiltIns` option without declaring a core-js version. Currently, we assume version 2.x when no version is passed. Since this default version will likely change in future versions of Babel, we recommend explicitly setting the core-js version you are using via the `corejs` option.

You should also be sure that the version you pass to the `corejs` option matches the version specified in your `package.json`'s `dependencies` section. If it doesn't, you need to run one of the following commands:

  npm install --save core-js@2    npm install --save core-js@3
  yarn add core-js@2              yarn add core-js@3

info => manager built (12 s)
WARN asset size limit: The following asset(s) exceed the recommended size limit (244 KiB).
WARN This can impact web performance.
WARN Assets:
WARN   vendors~main.5968ba64a9fc05fc720f.bundle.js (1.21 MiB)
WARN entrypoint size limit: The following entrypoint(s) combined asset size exceeds the recommended limit (244 KiB). This can impact web performance.

WARN For more info visit https://webpack.js.org/guides/code-splitting/
info => Building preview..
info => Loading preview config..
info => Loading presets
info => Using default webpack setup.
info => Loading create-react-app config.
info => Compiling preview..
info => Preview built (7.05 s)
WARN asset size limit: The following asset(s) exceed the recommended size limit (244 KiB).
WARN This can impact web performance.
WARN Assets:
WARN   vendors~main.8083339303bc8e5ec295.bundle.js (592 KiB)
WARN entrypoint size limit: The following entrypoint(s) combined asset size exceeds the recommended limit (244 KiB). This can impact web performance.

WARN For more info visit https://webpack.js.org/guides/code-splitting/

@shilman I just stumbled across this same problem. It seems to be an issue with the order in which npm resolves the webpack dependencies. If you do a fresh install of create-react-app and storybook v5, it works as expected. However, if you have a slightly different package.json file, and npm resolves the webpack dependency from storybook v5 before it resolves the webpack dependency from react-scripts, it generates the error about incompatible versions.
I believe I've created a reliable reproduction in this repo.
https://github.com/trevoreyre/storybook-issue-6161

@trevoreyre @shilman Hey!  Tried to track down a solution still but coming up short...getting the same error even after downgrading storybook and react scripts, seems webpack just doesn't want to line up versions

Cc @mrmckeb

@jacobgranberry If you set up a new CRA from scratch and then add storybook to it, does it work for you?

@shilman yes - seems to work as expected when created from scratch

@shilman @trevoreyre
I believe I've figured it out.  React-scripts needs to be in dependencies, not DevDependencies. I believe storybook requires some polyfills that are not built/included by CRA if its in devdependencies.

Great! :+1:

oh man, @jacobgranberry thank you very much!

@jacobgranberry That's correct, and it should never be a devDependency. It was a design decision by Joe and Dan early on in the CRA project.


tuple shape mismatch error while training

before d gen
2
4
2048
before d real
2
4
2048
2018-07-03 11:11:01.074867: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-07-03 11:11:01.117290: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1356] Found device 0 with properties:
name: Quadro K420 major: 3 minor: 0 memoryClockRate(GHz): 0.8755
pciBusID: 0000:03:00.0
totalMemory: 1.94GiB freeMemory: 1.35GiB
2018-07-03 11:11:01.117324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Ignoring visible gpu device (device: 0, name: Quadro K420, pci bus id: 0000:03:00.0, compute capability: 3.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
2018-07-03 11:11:01.117336: I tensorflow/core/common_runtime/gpu/gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-07-03 11:11:01.117346: I tensorflow/core/common_runtime/gpu/gpu_device.cc:929]      0
2018-07-03 11:11:01.117353: I tensorflow/core/common_runtime/gpu/gpu_device.cc:942] 0:   N
2018-07-03 11:11:02.343335: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.412697: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.428441: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.428441: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.429115: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.437389: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.437405: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.441379: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.449401: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.451722: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.457215: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.457665: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.458851: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:02.459306: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:03.544010: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
2018-07-03 11:11:03.636651: W tensorflow/core/framework/op_kernel.cc:1318] OP_REQUIRES failed at queue_ops.cc:105 : Invalid argument: Shape mismatch in tuple component 1. Expected [128,128,1], got [128,128,3]
Traceback (most recent call last):
File "train.py", line 158, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 154, in main
train()
File "train.py", line 89, in train
_, g_loss_value, d_loss_value = sess.run([train_op, dcgan.losses['g'], dcgan.losses['d']])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 900, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1316, in _do_run
run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: RandomShuffleQueue '_2_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 64, current size 0)
[[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]
Caused by op u'shuffle_batch', defined at:
File "train.py", line 158, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 154, in main
train()
File "train.py", line 54, in train
images, segmentation_images = load_image_and_segmentation_from_idlist(idlist_tensor_img, idlist_tensor_seg, batch_size, 16, 2560, shift_params = [-128, -0.5], rescale_params = [128, 0.5], shuffle = True)
File "/home/nikhitha/Srijita_work/Image_Preprocess/Generative-Adversarial-Network-based-Synthesis-for-Supervised-Medical-Image-Segmentation-master/load_folder_images.py", line 84, in load_image_and_segmentation_from_idlist
min_after_dequeue=min_queue_examples)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 1300, in shuffle_batch
name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 846, in _shuffle_batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/data_flow_ops.py", line 483, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 3480, in queue_dequeue_many_v2
component_types=component_types, timeout_ms=timeout_ms, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 3392, in create_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1718, in init
self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access
OutOfRangeError (see above for traceback): RandomShuffleQueue '_2_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 64, current size 0)
[[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]
Hi , I am getting this tuple shape mismatch error , can you please provide me with the solution to this ?
It is urgent .

Hi,
based on your error log, I suspect that either your images or segmentation masks are not single-channel, but are instead stored as RGB images. You will have to either change the network architecture to handle RGB images (and remove the set_shape call in load_folder_images) or make sure your images are single-channel via tensorflow functions or manual preprocessing. (This needs to be done before the set_shape call in decode_and_preprocess_image).
Additionally, it seems like your GPU is ignored because its compute capability is too low - I have never tested/run this on a CPU, so you might encounter operations that are not supported on the CPU and it might just not work at all.

@thomasneff
I did not get a tuple mismatch error, but I did get a RandomShuffleQueue error. I posted about this in another issue to your code.
Here, you mentioned that images need to be single channel or the code needs to be altered to handle RGB images. In my case, images are single-channel. They are taken from the ISBI EM 2012 challenge and are gray scale images with dimensions 512-by-512.
Then why am I getting the error? Please read about my issue in https://github.com/thomasneff/Generative-Adversarial-Network-based-Synthesis-for-Supervised-Medical-Image-Segmentation/issues/7

Hi,
your referenced issue sounds similar to #1 , where the file names/folder names were not set to what the code expects. You can probably verify if this is the case by stepping through the initial part where the shuffle queues are setup from the file paths and checking if the files are found correctly. (e.g. check if string_tensor_from_idlist_and_path returns a valid string tensor of filenames and/or check if the filenames are parsed correctly.)

Hi @thomasneff
I looked into https://github.com/thomasneff/Generative-Adversarial-Network-based-Synthesis-for-Supervised-Medical-Image-Segmentation/issues/1 and followed it thoroughly. I have done everything that is asked for there, except that my files are in jpg instead of png.
So I converted my files to PNG and tried again. But I'm getting the same error. I printed the file names in util.py to see of correct names are being read.
Printing size of images and labels...
(128, 128, 128, 1)
(128, 128, 128, 1)
before d gen
2
4
2048
before d real
2
4
2048
2018-09-04 22:34:14.877201: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-04 22:34:14.947844: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:898] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-09-04 22:34:14.948125: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1344] Found device 0 with properties:
name: GeForce GTX 980 Ti major: 5 minor: 2 memoryClockRate(GHz): 1.076
pciBusID: 0000:01:00.0
totalMemory: 5.93GiB freeMemory: 5.56GiB
2018-09-04 22:34:14.948138: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1423] Adding visible gpu devices: 0
2018-09-04 22:34:15.127788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-09-04 22:34:15.127819: I tensorflow/core/common_runtime/gpu/gpu_device.cc:917]      0
2018-09-04 22:34:15.127825: I tensorflow/core/common_runtime/gpu/gpu_device.cc:930] 0:   N
2018-09-04 22:34:15.127993: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5338 MB memory) -> physical GPU (device: 0, name: GeForce GTX 980 Ti, pci bus id: 0000:01:00.0, compute capability: 5.2)
Traceback (most recent call last):
File "train.py", line 156, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 152, in main
train()
File "train.py", line 87, in train
_, g_loss_value, d_loss_value = sess.run([train_op, dcgan.losses['g'], dcgan.losses['d']])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 905, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1140, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1321, in _do_run
run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: RandomShuffleQueue '_2_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 128, current size 0)
[[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]
Caused by op u'shuffle_batch', defined at:
File "train.py", line 156, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 152, in main
train()
File "train.py", line 51, in train
images, segmentation_images = load_image_and_segmentation_from_idlist(idlist_tensor_img, idlist_tensor_seg, batch_size, 16, 2560, shift_params = [-128, -0.5], rescale_params = [128, 0.5], shuffle = True)
File "/home/aditi/Documents/PhD/Steel_Seg/Data/Ground-Truth-Generation/GAN_trained_to_get_GT/Generative-Adversarial-Network-based-Synthesis-for-Supervised-Medical-Image-Segmentation-master/load_folder_images.py", line 92, in load_image_and_segmentation_from_idlist
min_after_dequeue=min_queue_examples)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 1301, in shuffle_batch
name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 847, in _shuffle_batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/data_flow_ops.py", line 483, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 3476, in queue_dequeue_many_v2
component_types=component_types, timeout_ms=timeout_ms, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1654, in init
self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access
OutOfRangeError (see above for traceback): RandomShuffleQueue '_2_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 128, current size 0)
[[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]
Is there any other variable that I could print out and check to see if images are being read properly? How do I solve this? Please help.

Hi,
try using absolute paths (i.e. /home/.../.../train-images/) instead of relative paths - it's been a while so I don't know how Linux/string_tensor_from_idlist_and_path expects the paths.

Hi,
then I'm not sure what else to suggest - the error ( "(requested 128, current size 0)") definitely suggests that something with the image loading isn't working.
You could try to load an image using the paths you're outputting manually and see if this works - similar to what is done in load_image in load_folder_images.py.
For example, try to take one of your file paths that you outputted before, and use a tf.WholeFileReader to read it. Check if this works. Then check if tf.image.decode_png works for this file.

@thomasneff I could get it running finally. There was error in file names. Apparently, if the name does not contain ".png", then ids.txt file should also not contain ".png".
Chnaged that one thing and now it's training.
Thank you so much for your prompt response. Much appreciated :)
I will bug you again if I face more problems with this code base. Thanks again !

@appyfizzA  i am having the same error and when i delete the path for .txt file and just put the name , this error rise
idlist_img_name = 'imagetxt.txt'
idlist_seg_name = 'labeltext.txt'
IOError: [Errno 2] No such file or directory: 'imagetxt.txt'
what did you do to make it work

Hi,
based on your error log, I suspect that either your images or segmentation masks are not single-channel, but are instead stored as RGB images. You will have to either change the network architecture to handle RGB images (and remove the set_shape call in load_folder_images) or make sure your images are single-channel via tensorflow functions or manual preprocessing. (This needs to be done before the set_shape call in decode_and_preprocess_image).
Additionally, it seems like your GPU is ignored because its compute capability is too low - I have never tested/run this on a CPU, so you might encounter operations that are not supported on the CPU and it might just not work at all.

Hi @thomasneff , can you help how can we make it run with rgb images. What changes we need exactly to get the network working for rgb


Vertices draw off into infinity

Please check if your issue is not a duplicate by searching existing issues
Describe the bug
Sometimes when approaching the edge of a chunk I've experienced vertices seem to stretch out into somewhere far in the distance. This sometimes affects tiles near the player as they flicker and disappear or have extra shadows appear. I've also noticed this in a lot of caves in game.
To Reproduce
Steps to reproduce the behavior:

Approach the edge of a chunk.
See the stretching of polygons.

Expected behavior
There should be no stretching of polygons.
Screenshots
Here you can see the triangles stretch off beyond the horizon.
These also cast shadows on nearby tiles, as seen in the first image.
The second image shows a bridge in the top left which has been effected by the bug.

As you can see this still happens on small draw distances (20) and has affected the tree.

Environment (please complete the following information):

OS: Windows 10.0.19042
RuneLite version: 1.7.25
Launcher version: 2.1.7

Hardware:

GPU: Gigabyte GeForce 3080 Turbo
CPU: Ryzen 5900X

Related to #209.

An update was released today that should have fixed this. :)


CNS-799: uint conversions and static analysis tools fixes

The static analysis commands used:
golangci-lint run --disable-all --enable gosec,govet,staticcheck
golangci-lint run --disable-all --presets bugs ./x/... -v

Are you sure that the command you ran run staticcheck? Because I ran staticcheck and I get more errors about unused functions, unused consts etc.

I ran it through golangci-lint as shown above. You're right, running the actual staticcheck does output more errors. These will not be handled here


Harpy isn't working right now

Hey there, it looks like everything is good on our implementation. But for some reason it's not notifying users to update. Do you have any idea what might be happening?

Need more info. Can you provide me with your App Store ID for the app? Also, is it in the US App Store?

Yes, it is in the US app store. This is our app ID: 923798849. We were stepping through the code and we saw that Harpy formats an app store url to get the version information and when we checked the url on the web browser on a phone and laptop it was the correct version. but when we added a breakpoint in the code and ran it, it showed the old version in the json blob.

What version of Harpy are you using? The latest?

I ask about the version because I fixed the bug that may be causing this issue a while back: https://github.com/ArtSabintsev/Harpy/blob/master/Harpy/Harpy.m#L151

We are not on the latest. I think that might be the issue. Thanks for your help.

Thanks for following up. Good luck!