Running Gradle task 'assembleDebug'...

Steps to Reproduce

I ran 'flutter run' and 'flutter run -v' (this is my first time in mobile development no experience in mobile development)
And then it just stay that ways for a long time
I have tried disable my firewall and it still the same

Logs

run 'flutter run'

logs
Launching lib\main.dart on RMX1941 in debug mode...
Running Gradle task 'assembleDebug'...
Exception in thread "main" java.lang.RuntimeException: Timeout of 120000 reached waiting for exclusive access to file: C:\Users\azrir\.gradle\wrapper\dists\gradle-5.6.2-all\9st6wgf78h16so49nn74lgtbb\gradle-5.6.2-all.zip
        at org.gradle.wrapper.ExclusiveFileAccessManager.access(ExclusiveFileAccessManager.java:61)
        at org.gradle.wrapper.Install.createDist(Install.java:48)
        at org.gradle.wrapper.WrapperExecutor.execute(WrapperExecutor.java:128)
        at org.gradle.wrapper.GradleWrapperMain.main(GradleWrapperMain.java:61)
Running Gradle task 'assembleDebug'...
Running Gradle task 'assembleDebug'... Done                       122.5s (!)
[!] Gradle threw an error while downloading artifacts from the network. Retrying to download...
Exception in thread "main" java.lang.RuntimeException: Timeout of 120000 reached waiting for exclusive access to file: C:\Users\azrir\.gradle\wrapper        at org.gradle.wrapper.ExclusiveFileAccessManager.access(ExclusiveFileAccessManager.java:61)
        at org.gradle.wrapper.Install.createDist(Install.java:48)
        at org.gradle.wrapper.WrapperExecutor.execute(WrapperExecutor.java:128)
Running Gradle task 'assembleDebug'...
Running Gradle task 'assembleDebug'... Done                       121.3s (!)
[!] Gradle threw an error while downloading artifacts from the network. Retrying to download...
Exception: Gradle task assembleDebug failed with exit code 1
2. Log when run 'flutter run -v'

[ +588 ms] executing: [C:\Program Files\flutter/] git -c log.showSignature=false log -n 1 --pretty=format:%H
[ +350 ms] Exit code 0 from: git -c log.showSignature=false log -n 1 --pretty=format:%H
[   +2 ms] 2ae34518b87dd891355ed6c6ea8cb68c4d52bb9d
[   +3 ms] executing: [C:\Program Files\flutter/] git tag --contains HEAD
[ +814 ms] Exit code 0 from: git tag --contains HEAD
[   +1 ms] 1.20.1
[  +37 ms] executing: [C:\Program Files\flutter/] git rev-parse --abbrev-ref --symbolic @{u}
[ +185 ms] Exit code 0 from: git rev-parse --abbrev-ref --symbolic @{u}
[   +2 ms] origin/stable
[   +1 ms] executing: [C:\Program Files\flutter/] git ls-remote --get-url origin
[ +222 ms] Exit code 0 from: git ls-remote --get-url origin
[   +2 ms] https://github.com/flutter/flutter.git
[ +351 ms] executing: [C:\Program Files\flutter/] git rev-parse --abbrev-ref HEAD
[ +277 ms] Exit code 0 from: git rev-parse --abbrev-ref HEAD
[  +11 ms] stable
[ +308 ms] Artifact Instance of 'AndroidMavenArtifacts' is not required, skipping update.
[   +2 ms] Artifact Instance of 'AndroidGenSnapshotArtifacts' is not required, skipping update.
[   +2 ms] Artifact Instance of 'AndroidInternalBuildArtifacts' is not required, skipping update.
[  +31 ms] Artifact Instance of 'IOSEngineArtifacts' is not required, skipping update.
[   +3 ms] Artifact Instance of 'FlutterWebSdk' is not required, skipping update.
[  +21 ms] Artifact Instance of 'WindowsEngineArtifacts' is not required, skipping update.
[  +61 ms] Artifact Instance of 'MacOSEngineArtifacts' is not required, skipping update.
[   +2 ms] Artifact Instance of 'LinuxEngineArtifacts' is not required, skipping update.
[  +46 ms] Artifact Instance of 'LinuxFuchsiaSDKArtifacts' is not required, skipping update.
[  +43 ms] Artifact Instance of 'MacOSFuchsiaSDKArtifacts' is not required, skipping update.
[   +2 ms] Artifact Instance of 'FlutterRunnerSDKArtifacts' is not required, skipping update.
[   +1 ms] Artifact Instance of 'FlutterRunnerDebugSymbols' is not required, skipping update.
[  +92 ms] executing: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe devices -l
[ +158 ms] List of devices attached
                    INU8H67HEMTSU8GY       device product:RMX1941 model:RMX1941 device:RMX1941 transport_id:13
[  +31 ms] C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe -s INU8H67HEMTSU8GY shell getprop
[ +284 ms] Artifact Instance of 'AndroidMavenArtifacts' is not required, skipping update.
[  +23 ms] Artifact Instance of 'AndroidInternalBuildArtifacts' is not required, skipping update.
[  +28 ms] Artifact Instance of 'IOSEngineArtifacts' is not required, skipping update.
[   +2 ms] Artifact Instance of 'FlutterWebSdk' is not required, skipping update.
[  +92 ms] Artifact Instance of 'WindowsEngineArtifacts' is not required, skipping update.
[  +37 ms] Artifact Instance of 'MacOSEngineArtifacts' is not required, skipping update.
[   +2 ms] Artifact Instance of 'LinuxEngineArtifacts' is not required, skipping update.
[   +1 ms] Artifact Instance of 'LinuxFuchsiaSDKArtifacts' is not required, skipping update.
[   +4 ms] Artifact Instance of 'MacOSFuchsiaSDKArtifacts' is not required, skipping update.
[ +161 ms] Artifact Instance of 'FlutterRunnerSDKArtifacts' is not required, skipping update.
[  +50 ms] Artifact Instance of 'FlutterRunnerDebugSymbols' is not required, skipping update.
[ +877 ms] Generating C:\Users\azrir\Desktop\sideProject\flutter\test_app\android\app\src\main\java\io\flutter\plugins\GeneratedPluginRegistrant.java[ +133 ms] ro.hardware = mt6765
[   +2 ms] ro.build.characteristics = default
[ +239 ms] Starting incremental build...
[  +13 ms] Initializing file store
[ +103 ms] Skipping target: gen_localizations
[  +53 ms] complete
[  +25 ms] Launching lib\main.dart on RMX1941 in debug mode...
[  +51 ms] C:\Program Files\flutter\bin\cache\dart-sdk\bin\dart.exe --disable-dart-dev C:\Program
Files\flutter\bin\cache\artifacts\engine\windows-x64\frontend_server.dart.snapshot --sdk-root C:\Program
Files\flutter\bin\cache\artifacts\engine\common\flutter_patched_sdk/ --incremental --target=flutter --debugger-module-names
-Ddart.developer.causal_async_stacks=true --output-dill C:\Users\azrir\AppData\Local\Temp\flutter_tools.93cd3b04\flutter_tool.fcff848\app.dill
--packages .packages -Ddart.vm.profile=false -Ddart.vm.product=false
--bytecode-options=source-positions,local-var-info,debugger-stops,instance-field-initializers,keep-unreachable-code,avoid-closure-call-instructions
--enable-asserts --track-widget-creation --filesystem-scheme org-dartlang-root --initialize-from-dill build\cache.dill.track.dill
[ +114 ms] executing: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe -s INU8H67HEMTSU8GY shell -x logcat -v time -t 1
[ +211 ms] Exit code 0 from: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe -s INU8H67HEMTSU8GY shell -x logcat -v time -t 1
[   +2 ms] --------- beginning of main
           08-11 21:40:08.269 D/TrafficStatsHelper( 1728): transmitted_validWifiData.get(0) = wlan0
[  +52 ms] executing: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe -s INU8H67HEMTSU8GY shell -x logcat -v time -t 1
[ +299 ms] Exit code 0 from: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe -s INU8H67HEMTSU8GY shell -x logcat -v time -t 1
[   +9 ms] --------- beginning of main
           08-11 21:40:08.324 I/ADB_SERVICES(31256): post waitpid (pid=31344) status=0000
[ +143 ms] <- compile package:test_app/main.dart
[  +86 ms] executing: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe version
[ +856 ms] Android Debug Bridge version 1.0.41
                    Version 30.0.4-6686687
                    Installed as C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe
[ +118 ms] executing: C:\Users\azrir\AppData\Local\Android\sdk\platform-tools\adb.exe start-server
[ +412 ms] Building APK
[ +174 ms] Running Gradle task 'assembleDebug'...
[ +117 ms] gradle.properties already sets `android.enableR8`
[  +22 ms] Using gradle from C:\Users\azrir\Desktop\sideProject\flutter\test_app\android\gradlew.bat.
[  +51 ms] C:\Users\azrir\Desktop\sideProject\flutter\test_app\android\gradlew.bat mode: 33279 rwxrwxrwx.
[  +87 ms] executing: C:\Program Files\Android\Android Studio\jre\bin\java -version
[ +603 ms] Exit code 0 from: C:\Program Files\Android\Android Studio\jre\bin\java -version
[   +2 ms] openjdk version "1.8.0_242-release"
           OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b01)
           OpenJDK 64-Bit Server VM (build 25.242-b01, mixed mode)
[  +63 ms] executing: [C:\Users\azrir\Desktop\sideProject\flutter\test_app\android/]
C:\Users\azrir\Desktop\sideProject\flutter\test_app\android\gradlew.bat -Pverbose=true -Ptarget-platform=android-arm64
-Ptarget=C:\Users\azrir\Desktop\sideProject\flutter\test_app\lib\main.dart -Ptrack-widget-creation=true -Pfilesystem-scheme=org-dartlang-root
assembleDebug
[+1201629 ms] FAILURE: Build failed with an exception.
[ +272 ms] * What went wrong:
[   +6 ms] A problem occurred configuring root project 'android'.
[   +1 ms] > Could not resolve all artifacts for configuration ':classpath'.
[   +2 ms]    > Could not download kotlin-compiler-embeddable.jar (org.jetbrains.kotlin:kotlin-compiler-embeddable:1.3.50)
[   +1 ms]       > Could not get resource
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-compiler-embeddable/1.3.50/kotlin-compiler-embeddable-1.3.50.jar'.
[  +44 ms]          > Could not GET
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-compiler-embeddable/1.3.50/kotlin-compiler-embeddable-1.3.50.jar'.
[   +6 ms]             > jcenter.bintray.com
[   +1 ms]    > Could not download httpcore.jar (org.apache.httpcomponents:httpcore:4.4.10)
[   +8 ms]       > Could not get resource 'https://jcenter.bintray.com/org/apache/httpcomponents/httpcore/4.4.10/httpcore-4.4.10.jar'.
[   +9 ms]          > Could not GET 'https://jcenter.bintray.com/org/apache/httpcomponents/httpcore/4.4.10/httpcore-4.4.10.jar'.
[  +16 ms]             > jcenter.bintray.com
[   +8 ms]    > Could not download antlr4.jar (org.antlr:antlr4:4.5.3)
[   +1 ms]       > Could not get resource 'https://jcenter.bintray.com/org/antlr/antlr4/4.5.3/antlr4-4.5.3.jar'.
[   +1 ms]          > Could not GET 'https://jcenter.bintray.com/org/antlr/antlr4/4.5.3/antlr4-4.5.3.jar'.
[   +1 ms]             > jcenter.bintray.com
[   +5 ms]    > Could not download commons-io.jar (commons-io:commons-io:2.4)
[   +4 ms]       > Could not get resource 'https://jcenter.bintray.com/commons-io/commons-io/2.4/commons-io-2.4.jar'.
[  +19 ms]          > Could not GET 'https://jcenter.bintray.com/commons-io/commons-io/2.4/commons-io-2.4.jar'.
[ +103 ms]             > jcenter.bintray.com
[   +2 ms]    > Could not download juniversalchardet.jar (com.googlecode.juniversalchardet:juniversalchardet:1.0.3)
[   +2 ms]       > Could not get resource
'https://jcenter.bintray.com/com/googlecode/juniversalchardet/juniversalchardet/1.0.3/juniversalchardet-1.0.3.jar'.
[   +8 ms]          > Could not GET
'https://jcenter.bintray.com/com/googlecode/juniversalchardet/juniversalchardet/1.0.3/juniversalchardet-1.0.3.jar'.
[  +10 ms]             > jcenter.bintray.com
[   +5 ms]    > Could not download javapoet.jar (com.squareup:javapoet:1.8.0)
[   +2 ms]       > Could not get resource 'https://jcenter.bintray.com/com/squareup/javapoet/1.8.0/javapoet-1.8.0.jar'.
[  +13 ms]          > Could not GET 'https://jcenter.bintray.com/com/squareup/javapoet/1.8.0/javapoet-1.8.0.jar'.
[   +2 ms]             > jcenter.bintray.com
[   +6 ms]    > Could not download proguard-base.jar (net.sf.proguard:proguard-base:6.0.3)
[   +7 ms]       > Could not get resource 'https://jcenter.bintray.com/net/sf/proguard/proguard-base/6.0.3/proguard-base-6.0.3.jar'.
[   +5 ms]          > Could not GET 'https://jcenter.bintray.com/net/sf/proguard/proguard-base/6.0.3/proguard-base-6.0.3.jar'.
[   +5 ms]             > jcenter.bintray.com
[   +8 ms]    > Could not download auto-value.jar (com.google.auto.value:auto-value:1.5.2)
[   +4 ms]       > Could not get resource 'https://jcenter.bintray.com/com/google/auto/value/auto-value/1.5.2/auto-value-1.5.2.jar'.
[   +3 ms]          > Could not GET 'https://jcenter.bintray.com/com/google/auto/value/auto-value/1.5.2/auto-value-1.5.2.jar'.
[   +4 ms]             > jcenter.bintray.com
[   +4 ms]    > Could not download error_prone_annotations.jar (com.google.errorprone:error_prone_annotations:2.3.1)
[   +4 ms]       > Could not get resource
'https://jcenter.bintray.com/com/google/errorprone/error_prone_annotations/2.3.1/error_prone_annotations-2.3.1.jar'.
[   +9 ms]          > Could not GET
'https://jcenter.bintray.com/com/google/errorprone/error_prone_annotations/2.3.1/error_prone_annotations-2.3.1.jar'.
[ +482 ms]             > jcenter.bintray.com
[  +70 ms]    > Could not download jdom2.jar (org.jdom:jdom2:2.0.6)
[ +152 ms]       > Could not get resource 'https://jcenter.bintray.com/org/jdom/jdom2/2.0.6/jdom2-2.0.6.jar'.
[  +69 ms]          > Could not GET 'https://jcenter.bintray.com/org/jdom/jdom2/2.0.6/jdom2-2.0.6.jar'.
[ +143 ms]             > jcenter.bintray.com
[+1609 ms]    > Could not download kotlin-script-runtime.jar (org.jetbrains.kotlin:kotlin-script-runtime:1.3.50)
[  +10 ms]       > Could not get resource
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-script-runtime/1.3.50/kotlin-script-runtime-1.3.50.jar'.
[  +93 ms]          > Could not GET 'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-script-runtime/1.3.50/kotlin-script-runtime-1.3.50.jar'.[ +110 ms]             > jcenter.bintray.com
[ +409 ms]    > Could not download kotlin-daemon-embeddable.jar (org.jetbrains.kotlin:kotlin-daemon-embeddable:1.3.50)
[  +16 ms]       > Could not get resource
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-daemon-embeddable/1.3.50/kotlin-daemon-embeddable-1.3.50.jar'.
[ +107 ms]          > Could not GET
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-daemon-embeddable/1.3.50/kotlin-daemon-embeddable-1.3.50.jar'.
[ +129 ms]             > jcenter.bintray.com
[   +4 ms]    > Could not download trove4j.jar (org.jetbrains.intellij.deps:trove4j:1.0.20181211)
[   +4 ms]       > Could not get resource 'https://jcenter.bintray.com/org/jetbrains/intellij/deps/trove4j/1.0.20181211/trove4j-1.0.20181211.jar'.
[ +167 ms]          > Could not GET 'https://jcenter.bintray.com/org/jetbrains/intellij/deps/trove4j/1.0.20181211/trove4j-1.0.20181211.jar'.
[ +117 ms]             > jcenter.bintray.com
[  +23 ms]    > Could not download kotlin-build-common.jar (org.jetbrains.kotlin:kotlin-build-common:1.3.50)
[  +70 ms]       > Could not get resource
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-build-common/1.3.50/kotlin-build-common-1.3.50.jar'.
[  +83 ms]          > Could not GET 'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-build-common/1.3.50/kotlin-build-common-1.3.50.jar'.
[  +87 ms]             > jcenter.bintray.com
[  +68 ms]    > Could not download kotlinx-coroutines-core.jar (org.jetbrains.kotlinx:kotlinx-coroutines-core:1.1.1)
[  +75 ms]       > Could not get resource
'https://jcenter.bintray.com/org/jetbrains/kotlinx/kotlinx-coroutines-core/1.1.1/kotlinx-coroutines-core-1.1.1.jar'.
[   +3 ms]          > Could not GET
'https://jcenter.bintray.com/org/jetbrains/kotlinx/kotlinx-coroutines-core/1.1.1/kotlinx-coroutines-core-1.1.1.jar'.
[ +246 ms]             > jcenter.bintray.com
[   +5 ms]    > Could not download kotlin-stdlib-common.jar (org.jetbrains.kotlin:kotlin-stdlib-common:1.3.50)
[  +69 ms]       > Could not get resource
'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-stdlib-common/1.3.50/kotlin-stdlib-common-1.3.50.jar'.
[  +73 ms]          > Could not GET 'https://jcenter.bintray.com/org/jetbrains/kotlin/kotlin-stdlib-common/1.3.50/kotlin-stdlib-common-1.3.50.jar'.
[   +3 ms]             > jcenter.bintray.com
[   +3 ms]    > Could not download annotations.jar (org.jetbrains:annotations:13.0)
[ +237 ms]       > Could not get resource 'https://jcenter.bintray.com/org/jetbrains/annotations/13.0/annotations-13.0.jar'.
[   +3 ms]          > Could not GET 'https://jcenter.bintray.com/org/jetbrains/annotations/13.0/annotations-13.0.jar'.
[   +3 ms]             > jcenter.bintray.com
[   +2 ms]    > Could not download commons-compress.jar (org.apache.commons:commons-compress:1.12)
[  +70 ms]       > Could not get resource 'https://jcenter.bintray.com/org/apache/commons/commons-compress/1.12/commons-compress-1.12.jar'.
[  +69 ms]          > Could not GET 'https://jcenter.bintray.com/org/apache/commons/commons-compress/1.12/commons-compress-1.12.jar'.
[   +3 ms]             > jcenter.bintray.com
[   +2 ms]    > Could not download trove4j.jar (org.jetbrains.trove4j:trove4j:20160824)
[   +2 ms]       > Could not get resource 'https://jcenter.bintray.com/org/jetbrains/trove4j/trove4j/20160824/trove4j-20160824.jar'.
[   +3 ms]          > Could not GET 'https://jcenter.bintray.com/org/jetbrains/trove4j/trove4j/20160824/trove4j-20160824.jar'.
[  +75 ms]             > jcenter.bintray.com
[   +4 ms]    > Could not download kxml2.jar (net.sf.kxml:kxml2:2.3.0)
[ +112 ms]       > Could not get resource 'https://jcenter.bintray.com/net/sf/kxml/kxml2/2.3.0/kxml2-2.3.0.jar'.
[   +2 ms]          > Could not GET 'https://jcenter.bintray.com/net/sf/kxml/kxml2/2.3.0/kxml2-2.3.0.jar'.
[   +2 ms]             > jcenter.bintray.com
[  +85 ms]    > Could not download jsr305.jar (com.google.code.findbugs:jsr305:3.0.2)
[  +81 ms]       > Could not get resource 'https://jcenter.bintray.com/com/google/code/findbugs/jsr305/3.0.2/jsr305-3.0.2.jar'.
[  +70 ms]          > Could not GET 'https://jcenter.bintray.com/com/google/code/findbugs/jsr305/3.0.2/jsr305-3.0.2.jar'.
[  +67 ms]             > jcenter.bintray.com
[  +68 ms]    > Could not download failureaccess.jar (com.google.guava:failureaccess:1.0.1)
[ +145 ms]       > Could not get resource 'https://jcenter.bintray.com/com/google/guava/failureaccess/1.0.1/failureaccess-1.0.1.jar'.
[  +76 ms]          > Could not GET 'https://jcenter.bintray.com/com/google/guava/failureaccess/1.0.1/failureaccess-1.0.1.jar'.
[   +2 ms]             > jcenter.bintray.com
[   +2 ms]    > Could not download listenablefuture.jar (com.google.guava:listenablefuture:9999.0-empty-to-avoid-conflict-with-guava)
[  +73 ms]       > Could not get resource
'https://jcenter.bintray.com/com/google/guava/listenablefuture/9999.0-empty-to-avoid-conflict-with-guava/listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar'.
[   +6 ms]          > Could not GET
'https://jcenter.bintray.com/com/google/guava/listenablefuture/9999.0-empty-to-avoid-conflict-with-guava/listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar'.
[  +39 ms]             > jcenter.bintray.com
[  +42 ms]    > Could not download checker-qual.jar (org.checkerframework:checker-qual:2.5.2)
[   +2 ms]       > Could not get resource 'https://jcenter.bintray.com/org/checkerframework/checker-qual/2.5.2/checker-qual-2.5.2.jar'.
[   +2 ms]          > Could not GET 'https://jcenter.bintray.com/org/checkerframework/checker-qual/2.5.2/checker-qual-2.5.2.jar'.
[   +2 ms]             > jcenter.bintray.com
[ +144 ms]    > Could not download j2objc-annotations.jar (com.google.j2objc:j2objc-annotations:1.1)
[   +2 ms]       > Could not get resource 'https://jcenter.bintray.com/com/google/j2objc/j2objc-annotations/1.1/j2objc-annotations-1.1.jar'.
[   +7 ms]          > Could not GET 'https://jcenter.bintray.com/com/google/j2objc/j2objc-annotations/1.1/j2objc-annotations-1.1.jar'.
[  +73 ms]             > jcenter.bintray.com
[   +2 ms]    > Could not download animal-sniffer-annotations.jar (org.codehaus.mojo:animal-sniffer-annotations:1.17)
[   +2 ms]       > Could not get resource
'https://jcenter.bintray.com/org/codehaus/mojo/animal-sniffer-annotations/1.17/animal-sniffer-annotations-1.17.jar'.
[  +70 ms]          > Could not GET
'https://jcenter.bintray.com/org/codehaus/mojo/animal-sniffer-annotations/1.17/animal-sniffer-annotations-1.17.jar'.
[ +615 ms]             > jcenter.bintray.com
[  +56 ms]    > Could not download commons-logging.jar (commons-logging:commons-logging:1.2)
[+3024 ms]       > Could not get resource 'https://jcenter.bintray.com/commons-logging/commons-logging/1.2/commons-logging-1.2.jar'.
[ +695 ms]          > Could not GET 'https://jcenter.bintray.com/commons-logging/commons-logging/1.2/commons-logging-1.2.jar'.
[ +129 ms]             > jcenter.bintray.com
[  +16 ms]    > Could not download commons-codec.jar (commons-codec:commons-codec:1.10)
[   +2 ms]       > Could not get resource 'https://jcenter.bintray.com/commons-codec/commons-codec/1.10/commons-codec-1.10.jar'.
[   +2 ms]          > Could not GET 'https://jcenter.bintray.com/commons-codec/commons-codec/1.10/commons-codec-1.10.jar'.
[   +3 ms]             > jcenter.bintray.com
[   +3 ms]    > Could not download javax.activation.jar (com.sun.activation:javax.activation:1.2.0)
[ +678 ms]       > Could not get resource 'https://jcenter.bintray.com/com/sun/activation/javax.activation/1.2.0/javax.activation-1.2.0.jar'.
[ +124 ms]          > Could not GET 'https://jcenter.bintray.com/com/sun/activation/javax.activation/1.2.0/javax.activation-1.2.0.jar'.
[  +82 ms]             > jcenter.bintray.com
[   +3 ms]    > Could not download jaxb-runtime.jar (org.glassfish.jaxb:jaxb-runtime:2.2.11)
[ +105 ms]       > Could not get resource 'https://jcenter.bintray.com/org/glassfish/jaxb/jaxb-runtime/2.2.11/jaxb-runtime-2.2.11.jar'.
[   +3 ms]          > Could not GET 'https://jcenter.bintray.com/org/glassfish/jaxb/jaxb-runtime/2.2.11/jaxb-runtime-2.2.11.jar'.
[  +83 ms]             > jcenter.bintray.com
[  +97 ms]    > Could not download jaxb-core.jar (org.glassfish.jaxb:jaxb-core:2.2.11)
[ +164 ms]       > Could not get resource 'https://jcenter.bintray.com/org/glassfish/jaxb/jaxb-core/2.2.11/jaxb-core-2.2.11.jar'.
[   +3 ms]          > Could not GET 'https://jcenter.bintray.com/org/glassfish/jaxb/jaxb-core/2.2.11/jaxb-core-2.2.11.jar'.
[ +131 ms]             > jcenter.bintray.com
[ +166 ms]    > Could not download stax-ex.jar (org.jvnet.staxex:stax-ex:1.7.7)
[   +4 ms]       > Could not get resource 'https://jcenter.bintray.com/org/jvnet/staxex/stax-ex/1.7.7/stax-ex-1.7.7.jar'.
[ +340 ms]          > Could not GET 'https://jcenter.bintray.com/org/jvnet/staxex/stax-ex/1.7.7/stax-ex-1.7.7.jar'.
[  +87 ms]             > jcenter.bintray.com
[   +4 ms]    > Could not download FastInfoset.jar (com.sun.xml.fastinfoset:FastInfoset:1.2.13)
[  +81 ms]       > Could not get resource 'https://jcenter.bintray.com/com/sun/xml/fastinfoset/FastInfoset/1.2.13/FastInfoset-1.2.13.jar'.
[  +98 ms]          > Could not GET 'https://jcenter.bintray.com/com/sun/xml/fastinfoset/FastInfoset/1.2.13/FastInfoset-1.2.13.jar'.
[   +2 ms]             > jcenter.bintray.com
[   +2 ms]    > Could not download jaxb-api.jar (javax.xml.bind:jaxb-api:2.2.12-b140109.1041)
[  +82 ms]       > Could not get resource 'https://jcenter.bintray.com/javax/xml/bind/jaxb-api/2.2.12-b140109.1041/jaxb-api-2.2.12-b140109.1041.jar'.[  +78 ms]          > Could not GET 'https://jcenter.bintray.com/javax/xml/bind/jaxb-api/2.2.12-b140109.1041/jaxb-api-2.2.12-b140109.1041.jar'.
[   +5 ms]             > jcenter.bintray.com
[ +206 ms]    > Could not download txw2.jar (org.glassfish.jaxb:txw2:2.2.11)
[  +21 ms]       > Could not get resource 'https://jcenter.bintray.com/org/glassfish/jaxb/txw2/2.2.11/txw2-2.2.11.jar'.
[ +179 ms]          > Could not GET 'https://jcenter.bintray.com/org/glassfish/jaxb/txw2/2.2.11/txw2-2.2.11.jar'.
[ +123 ms]             > jcenter.bintray.com
[   +3 ms]    > Could not download istack-commons-runtime.jar (com.sun.istack:istack-commons-runtime:2.21)
[  +76 ms]       > Could not get resource 'https://jcenter.bintray.com/com/sun/istack/istack-commons-runtime/2.21/istack-commons-runtime-2.21.jar'.
[   +2 ms]          > Could not GET 'https://jcenter.bintray.com/com/sun/istack/istack-commons-runtime/2.21/istack-commons-runtime-2.21.jar'.
[   +3 ms]             > jcenter.bintray.com
[ +179 ms] * Try:
[  +37 ms] Run with --stacktrace option to get the stack trace. Run with --info or --debug option to get more log output. Run with --scan to get fullinsights.
[ +361 ms] * Get more help at https://help.gradle.org
[ +138 ms] BUILD FAILED in 20m 0s
[ +105 ms] Running Gradle task 'assembleDebug'... (completed in 1217.7s, longer than expected)
[ +156 ms] Exception: Gradle task assembleDebug failed with exit code 1
[  +44 ms] "flutter run" took 1,223,213ms.
[ +124 ms]
                    #0      throwToolExit (package:flutter_tools/src/base/common.dart:14:3)
                    #1      RunCommand.runCommand (package:flutter_tools/src/commands/run.dart:591:7)
                    <asynchronous suspension>
                    #2      FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:860:18)
                    <asynchronous suspension>
                    #3      FlutterCommand.run.<anonymous closure> (package:flutter_tools/src/runner/flutter_command.dart:741:33)
                    <asynchronous suspension>
                    #4      FlutterCommand.run.<anonymous closure> (package:flutter_tools/src/runner/flutter_command.dart)
                    #5      AppContext.run.<anonymous closure> (package:flutter_tools/src/base/context.dart:150:29)
                    #6      _rootRun (dart:async/zone.dart:1190:13)
                    #7      _CustomZone.run (dart:async/zone.dart:1093:19)
                    #8      _runZoned (dart:async/zone.dart:1630:10)
                    #9      runZoned (dart:async/zone.dart:1550:10)
                    #10     AppContext.run (package:flutter_tools/src/base/context.dart:149:18)
                    #11     FlutterCommand.run (package:flutter_tools/src/runner/flutter_command.dart:730:20)
                    #12     CommandRunner.runCommand (package:args/command_runner.dart:197:27)
                    #13     FlutterCommandRunner.runCommand.<anonymous closure> (package:flutter_tools/src/runner/flutter_command_runner.dart:332:21)                    #14     _rootRunUnary (dart:async/zone.dart:1198:47)
                    #15     _CustomZone.runUnary (dart:async/zone.dart:1100:19)
                    #16     _FutureListener.handleValue (dart:async/future_impl.dart:143:18)
                    #17     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:696:45)
                    #18     Future._propagateToListeners (dart:async/future_impl.dart:725:32)
                    #19     Future._completeWithValue (dart:async/future_impl.dart:529:5)
                    #20     _AsyncAwaitCompleter.complete (dart:async-patch/async_patch.dart:40:15)
                    #21     _completeOnAsyncReturn (dart:async-patch/async_patch.dart:311:13)
                    #22     FlutterVersion.checkFlutterVersionFreshness (package:flutter_tools/src/version.dart)
                    #23     _rootRunUnary (dart:async/zone.dart:1198:47)
                    #24     _CustomZone.runUnary (dart:async/zone.dart:1100:19)
                    #25     _FutureListener.handleValue (dart:async/future_impl.dart:143:18)
                    #26     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:696:45)
                    #27     Future._propagateToListeners (dart:async/future_impl.dart:725:32)
                    #28     Future._completeWithValue (dart:async/future_impl.dart:529:5)
                    #29     Future._asyncCompleteWithValue.<anonymous closure> (dart:async/future_impl.dart:567:7)
                    #30     _rootRun (dart:async/zone.dart:1190:13)
                    #31     _CustomZone.run (dart:async/zone.dart:1093:19)
                    #32     _CustomZone.runGuarded (dart:async/zone.dart:997:7)
                    #33     _CustomZone.bindCallbackGuarded.<anonymous closure> (dart:async/zone.dart:1037:23)
                    #34     _microtaskLoop (dart:async/schedule_microtask.dart:41:21)
                    #35     _startMicrotaskLoop (dart:async/schedule_microtask.dart:50:5)
                    #36     _runPendingImmediateCallback (dart:isolate-patch/isolate_patch.dart:118:13)
                    #37     _RawReceivePortImpl._handleMessage (dart:isolate-patch/isolate_patch.dart:169:5)

[ +651 ms] Running shutdown hooks
[   +8 ms] Shutdown hook priority 4
[  +10 ms] Shutdown hooks complete
[ +164 ms] exiting with code 1

Hi @Azri99
Looks like you're having issues with android packages, please switch to a different, make sure you internet connection isn't provide network.
Can you please provide your flutter doctor -v your flutter run --verbose and build.gradle from <flutter app>/android/.gradle
Thank you

Thank you for you help.And yeah apparently I put the flutter sdk at the place where they need administrator permission. After changing those location to a new one. It seems to be running just find


Update dependency versions to clear npm audit warnings

Version
What package version of the SDK are you using.
3.15
Describe the bug
Give a clear and concise description of what the bug is.
Versions of jsonwebtoken and base64url are out of date and cause "moderate" security warnings when running npm audit
To Reproduce
Clone the repo
npm i
npm audit
You will see moderate warnings about these packages.
Expected behavior
No warnings should be shown.
Screenshots

Additional context
Add any other context about the problem here.
[bug]
[javascript]

This commit appears to resolve this issue, but it appears these changes didn't get published to npm.

Confirmed: 3.15 was published 6 months ago, but the package was updated only 3 months ago.
We should publish 3.16 with this package update.


ALB create wirh error: attribute supports 2 item as a minimum

What happened?
Pulumi runtime: Python
reference to https://www.pulumi.com/registry/packages/alicloud/api-docs/alb/loadbalancer/
Create a ALB and got error if zone_mappings only config with one item
pulumi:pulumi:Stack: (same)
[urn=urn:pulumi:prod::v16team::pulumi:pulumi:Stack::my-prod]
error: alicloud:alb/loadBalancer:LoadBalancer resource 'my-alb' has a problem: zone_mappings: attribute supports 2 item as a minimum, config has 1 declared
Expected Behavior
Aliyun in region philippine(Manila) has only single AZ, it is impossible to create 2 items
Steps to reproduce
none
Output of pulumi about
CLI
Version      3.60.1
Go Version   go1.20.2
Go Compiler  gc
Plugins
NAME        VERSION
alicloud    3.33.0
aws         5.21.1
kubernetes  3.23.1
python      3.11.2
Host
OS       darwin
Version  13.2.1
Arch     arm64
Additional context
No response
Contributing
Vote on this issue by adding a 👍 reaction.
To contribute a fix for this issue, leave a comment (and link to your pull request, if you've opened one already).

Hi @twasa - I'm not sure you need to set the zone mappings at all if there is only one zone.
Can you see what happens if you leave out that field?
If you're still having trouble, can you send us a minimum reproduction that we can run on our end to further investigate?

TypeError: Missing required property 'zone_mappings'

try and find the tricky solution, just specific duplicate vswitch_id and zone_id
zone_mappings = [
alb.LoadBalancerZoneMappingArgs(
vswitch_id=vswitch1.id,
zone_id=vswitch1.zone_id
),
alb.LoadBalancerZoneMappingArgs(
vswitch_id=vswitch1.id,
zone_id=vswitch1.zone_id
),
]

It looks like this problem was solved.


Add external sources for events

Externally sourced event content:

community-meeting.md
meet-our-contributors.md
office-hours.md

/lgtm


10.0.19041.1741 [Not supported]

File upload: termsrv.zip

Hello! GitHub says that it doesn't support .dll files. I'd like to upload my termsrv.dll file as requested under other issues.

Duplicate of https://github.com/stascorp/rdpwrap/issues/1881


fix: generated image link jpg to jpeg

@hexojs/core
IMHO, this issue is high priority issue. Could you please review & merge this?
Problem
Hexo official site themes preview images can not see.
Reason
In html src image link extension is jpg. But, acturally (generated by gulp) image extension is jpeg. Please see below two images.

Others
Btw, I believe this issue caused by dependency package version. I propose include package-lock.json
Thanks

I agree with you. On this repo, we need a package-lock.json


ability to specify only my devices for webhooks

Thought this would be useful @dmiddlecamp

Hi @sjlu !
Thanks for the pull request, could you sign the CLA?
https://docs.google.com/a/spark.io/forms/d/1_2P-vRKGUFg5bmpcKLHO_qNZWGi5HKYnfrrkd-sbZoA/viewform
Thanks,
David

Done!
On Tue, Jan 13, 2015 at 1:42 PM, David Middlecamp
<EMAIL_ADDRESS>wrote:

Hi @sjlu !
Thanks for the pull request, could you sign the CLA?
https://docs.google.com/a/spark.io/forms/d/1_2P-vRKGUFg5bmpcKLHO_qNZWGi5HKYnfrrkd-sbZoA/viewform
Thanks,
David
Reply to this email directly or view it on GitHub:
https://github.com/spark/sparkjs/pull/43#issuecomment-69795698

thank you @sjlu! :smile_cat:  much appreciated.


CRD manifest for Upgrade

Hi team,
Previously my current version of cert-manager was 1.6.1 when I do the helm upgrade to 1.7.1 it was a success but by helm upgrade, crds wont be upgrading helm by itself can't do that so please provide a separate CRD manifest containing only CRDS to apply the latest version in the future.
helm 3 wont support that feature all the operator components also doing the same
https://helm.sh/docs/chart_best_practices/custom_resource_definitions/

We do provide CRDs in a separate manifest already with each GitHub release, see i.e assets for v1.7.1 release https://github.com/cert-manager/cert-manager/releases/tag/v1.7.1

Closing as I think this should be solved by the existing CRDs manifests


Rust template

Rust template project using cross-compilation

Built using sunodo 0.7.0 and machine starts successfully


[Windows] Possibly include (sym)links to current *.exe files in c:\Program Files\R\bin

In addition to the *.bat files in C:\Program Files\R\bin it would be great if there were also copies or symlinks to the current R.exe and RScript.exe.
I use Git Bash running in Windows Terminal (instead of PowerShell or CMD). This allows me to use the *nix style of almost everything without having to install WSL2. I ❤ that rig adds C:\Program Files\R\bin to the PATH and puts the current version of R in that location. It's very intuitive.
However, Git Bash doesn't recognize *.bat files as being executables (although you can run them if you type out the whole path).
I'm not a Rustacean, but I suspect that somewhere in sc_system_make_links() it would mean creating a symbolic link to the R.exe and Rscript.exe files in, e.g. C:\Program Files\R\R-4.3.1\bin. Is something like this pretty straightforward?
What I currently do now (manually) to achieve this:

Open Windows Terminal as administrator
Navigate to C:\Program Files\R
Create a symbolic link to the current version, e.g. ln -s ../R-4.3.1 current
Make sure that C:\Program Files\R\current\bin is added to my PATH

About My Setup
Windows 11 on x64. Installed rig with scoop. Using Git Bash profile inside of Windows Terminal as my default terminal environment.

I have some vague memories that symlinks didn't work well on Windows, that's why I started creating the .bat files. (On other platforms rig uses symlinks.)
But let me experiment with it, if is works for you, that's a good start. It is possible that they are OK on modern Windows, but not on older Windows, but then we could still use them on newer Windows.

Just upvoting this one! I'm loving rig as a project, but running into similar friction with just the .bat files specifically in conjunction with the Quarto VS Code extension. (I don't think details are really important, but happy to share if interested.) Right now, I'm solving for it by setting the QUARTO_R environment variable separately and pointing to the bin/ file for the specific version, but it's definitely less elegant than fully embracing rig

Its possible this is the symlink issue on Windows:

As opposed to symlinks, junction does not require administrator privileges during creation. (However starting with Windows 10 Insiders build 14972, symlinks can be created without needing to elevate the console as administrator)^1.

Mentioned here in the readme of junction https://crates.io/crates/junction

I think it was simply that older windows did not have symlinks at all. (rig initially supported Windows 7!) I think admins rights are ok, rig already needs to run as admin to change these links.


Is there a way to get RAM, CPU and Battery usage?

Is it possible to add stats for RAM, CPU and / or Battery usage for the processes listed?
thank you.

Package uses android.app.usage to collect usage events, and there are no properties related to RAM/CPU/Battery in that.
But by using other classes like ActivityManager.MemoryInfo and ActivityManager.html it might be possible.


LL-7232 update icon resources

Updated icon resources for splashscreen and app icons + loader on app boot
:warning: do not merge this until we’re sure it will be released on the correct date, to sync with product for the exact dates
Type

Feature
Context

LL-7232
Parts of the app affected / Test plan

Testing iOS for you since apple doesn't want you to do it on linux, this is how the splash and the icons look (that floating thing is the home button so you don't break the hardware one, nothing to do with us). I believe the icon on settings About should also use the new icon though.

I updated some icon and colors after syncing with design, to me it's ready to QA

Oh no, that's so ugly @ychen-ledger why did you do that!

Oh no, that's so ugly @ychen-ledger why did you do that!

it happened just as it was, sorry🥶

Oh no, that's so ugly @ychen-ledger why did you do that!

it happened just as it was, sorry🥶

I know, I was just teasing. I'm taking a look now

Can you take a look again @ychen-ledger ?
It's in theory a cache issue and renaming the assets should remove this first ghost old logo splash, but I can't test on a staging build myself. From what I see, it just goes black and then we have the animated logo thing 🤷🏼

Can you take a look again @ychen-ledger ? It's in theory a cache issue and renaming the assets should remove this first ghost old logo splash, but I can't test on a staging build myself. From what I see, it just goes black and then we have the animated logo thing 🤷🏼

@juan-cortes Thanks a lot, i'll do a double check🙈

🚀


Mode-line on screenshots

Great theme! Could you provide some information on you mode-line setup? It seems to go well with the rest of your theme. If that’s a powerline.el theme, you could consider providing that as part of the package.

Thanks. That is the Spacemacs modeline which is based on powerline AFAIK.
There is already an issue at the spacemacs repo asking for exactly what you want. So you can track the progress there.
You should also be able to find the necessary setup in the spacemacs source, but I've heard that it is not trivial to extract the modeline.

Thank you kindly for the pointer!


TimeXer是往因子挖掘上靠了吗

目前主要用条件因素来提升模型能力的时序模型不太常见。这一次是搞特征工程，下一步会不会就要上因子挖掘了来搞因果时序了呢，期待

Thanks a lot for your interest in our work. We will be happy to see this work in the relevant applications.

哥，都是中国人了就不必说英文了嘞

Thanks a lot for your interest in our work. We will be happy to see this work in the relevant applications.
哥，都是中国人了就不必说英文了嘞


Notify when secrets are about to expire

Preflight Checklist

[X] I could not find a solution in the existing issues, docs, nor discussions
[ ] I have joined the ZITADEL chat

Describe your problem
Managers can set expiry on service user secrets. When the secrets are not updated, that may break an application.
Describe your ideal solution
As a Manager/Creator or a secret, I want to be informed when (or prior to) that secret expires, so I can regenerate a secret and update my application.
The notification could be optional
Version
No response
Environment
ZITADEL Cloud
Additional Context
No response

Hi @mffap, what kind of notifications are you thinking of? email, webhooks, telegram messages... all of them :smile: something as suggested here: https://github.com/zitadel/zitadel/issues/6131?
My question for @hifabienne, does Zitadel have the included batteries for implementing async tasks like sending an alert?
In the past for a Python app I used a message queue to run jobs like sending notifications with Celery and RabbitMQ.
I suppose that for Zitadel I could start using something like https://github.com/go-co-op/gocron to add "cron" jobs to Zitadel that could send alerts but... @hifabienne what should be the best approach here for Zitadel: a task queue with workers like https://github.com/hibiken/asynq or something more in the line of NATS Jetstream?
I've no experience on this topic but I'd love to learn about it so if Zitadel has something in mind I can spend time studying it and implementing the solution you prefer
I feel that Zitadel really need something to work with sending emails, scheduled tasks, processing large datasets,
long-running operations...
Just let me know if you want me to work on this
Thanks!

I think starting with email notifications would be great.
We do already have a place wehere we do trigger notifications in a scheduled way. But not sure if thats the right way to go.
@livio-a @adlerhurst can you maybe help out with those questions and how we would like to implement something like this?


cosign: 1.11.0 -> 1.11.1

Description of changes

https://github.com/sigstore/cosign/releases/tag/v1.11.1
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
22.11 Release Notes (or backporting 22.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review run on x86_64-linux 1

1 package built:

cosign

Result of nixpkgs-review pr 188360 run on x86_64-linux 1

1 package built:

cosign


Add gh-access-token flag into backport script

The current backport script does not have github access token flag.
This patch will be useful when encountered rate limit issue.

Thanks!!

I was unable to create a backport for 1.22. @cloudchamb3r, please send one manually. :tea:
go run ./contrib/backport 32283
...  // fix git conflicts if any
go run ./contrib/backport --continue


1 year and 17 commits later...

1 year and 17 commits later...
it's time for a new release.
Happy x-mas for everyone :-)

I agree, I'll do it in the holiday days :)
Happpy x-mas!


Action is not waiting for codebuild run to end

I couldn't manage to make this action wait for codebuild run to end. It only starts the codebuild run and proceeds to the next step without waiting for the final result. I'm sharing the yml file snippet for the step and its output. Any help would be much appreciated.
      - name: Run CodeBuild
        uses: dark-mechanicum/aws-codebuild@v1
        env:
          CODEBUILD__sourceVersion: "publish"
        with:
          projectName: ${{ env.PROJECT_NAME }}

I don't know but can it be related to StartBuildInput?
I think here the reportBuildStatusOverride property is not set and it's undefined
Maybe explicitly setting it to true may help?

reportBuildStatus — (Boolean)
Set to true to report the status of a build's start and finish to your source provider. This option is valid only when your source provider is GitHub, GitHub Enterprise, or Bitbucket. If this is set and you use a different source provider, an invalidInputException is thrown.
To be able to report the build status to the source provider, the user associated with the source provider must have write access to the repo. If the user does not have write access, the build status cannot be updated. For more information, see Source provider access in the CodeBuild User Guide.
The status of a build triggered by a webhook is always reported to your source provider.
If your project's builds are triggered by a webhook, you must push a new commit to the repo for a change to this property to take effect.

@ozgenbaris1 potentially you can set it from your implementation of GitHub Action usage like:
  - name: Run CodeBuild
    uses: dark-mechanicum/aws-codebuild@v1
    env:
      CODEBUILD__sourceVersion: "publish"
      CODEBUILD__reportBuildStatusOverride: "true"
    with:
      projectName: ${{ env.PROJECT_NAME }}

Try this one. I will be happy to get any response about it :)

@ozgenbaris1 I've applied some fixes that will resolve wait for job status without logs. Try to use main version instead of v1 to verify is that will resolve your issue.
  - name: Run CodeBuild
    uses: dark-mechanicum/aws-codebuild@main
    env:
      CODEBUILD__sourceVersion: "publish"
    with:
      projectName: ${{ env.PROJECT_NAME }}

@akazakou Thanks for your time. Now I have two more issues :slightly_smiling_face:

My action can't read codebuild logs. It only tracks phase changes. How can I make it read the logs? I don't think it's related with the user permissions because I have full privilege. Can it be something else?

Can't find logs output for AWS CodeBuild job: prefect-sample-flow:e012b09a-8e7c-4daf-b916-9700531e175f

One of the phases in my codebuild throws an error (intentionally) But the github action proceeds to the next step and continues even though codebuild throws an error. I expect the action to also throw errors and set action status to fail. Are you planning to make some improvements about this? I can create another issue if you want.

@ozgenbaris1 I've added #43 PR that will fail the GitHub Action on AWS CodeBuild job.

If we are talking about the first question: here is a message telling us that in job configuration it can't find logs for parsing in job information description: https://github.com/dark-mechanicum/aws-codebuild/blob/main/src/codebuildjob.ts#L44-L57

@ozgenbaris1 I would appreciate it if you could check the latest changes and tell me if that helped you solve the problem.
The problem looks like you don't have CloudWatch logging enabled for your project. If they are still enabled, please check that they are actually being delivered to AWS CloudWatch.
If they are indeed being delivered to AWS CloudWatch, I will try to add debug functionality to GitHub Action so that you can have a more detailed test of GitHub Action behavior with advanced logging of requests to and responses received from the AWS API.

@ozgenbaris1 I've added debug logs for the current GitHub Action. An example of debug output you can find in the example run here
You can enable debug output in the re-run jobs window by enabling debug logs checkbox

If it will be possible, please upload here a debug output for analyzing the behavior of your implementation using the current GitHub action. You can download debug output by clicking the gears icon on the top right side of the action your workflow logs output.

@akazakou Thanks for your efforts! Actually I was creating my codebuild project via AWS CDK. I didn't specify any logging configurations, so going with the defaults. Project's logs settings is as follows (every part seems null). However, it sends logs to cloudwatch.

When I run codebuild's startBuild method, the response I'm getting is below. As you can see, there are lots of null parts both in deepLink and cloudWatchLogsArn
logs: {
    deepLink: 'https://console.aws.amazon.com/cloudwatch/home?region=<region>#logEvent:group=null;stream=null',
    cloudWatchLogsArn: 'arn:aws:logs:<region>:<account_id>:log-group:null:log-stream:null'
  }

Once I added logging configurations to my AWS CDK codebuild stack, the action runs without problem and I can read the logs from github actions. Would you prefer getting logs directly from cloudwatch itself by generating a custom cloudWatchLogsArn yourself rather than reading it from startBuild response?

@ozgenbaris1 that's awesome! Thank you for verification!

Would you prefer getting logs directly from cloudwatch itself by generating a custom cloudWatchLogsArn yourself rather than reading it from startBuild response?

Right now I'm doing this. If I can't find a correct configuration in response, I'm generating the default way to get logs. Only one thing is required: it flags that cloudwatch logs should be enabled. Because if that flag will not be enabled - it will not be delivered to the cloudwatch at all.
If you have some extended information on how to generate the correct CloudWatch ARN, I would be grateful to you :)

Seems that issue was resolved. I'll close it. In case of some other issues, please create a new issue here :)


Qt: Failed to create XKB context!, keyboard is missing in qt and this is the error which occures:

xkbcommon: ERROR: failed to add default include path auto
Qt: Failed to create XKB context!
Use QT_XKB_CONFIG_ROOT environmental variable to provide an additional search path, add ':' as separator to provide several search paths and/or make sure that XKB configuration data directory contains recent enough contents, to update please see http://cgit.freedesktop.org/xkeyboard-config/ .

One workaround for testers would be to set this var when launching qt for a test:
export QT_XKB_CONFIG_ROOT=/usr/share/X11/xkb && ./ion-qt

If you will launch the wallet many times, place this line into your profile definition:
export QT_XKB_CONFIG_ROOT=/usr/share/X11/xkb >> /home/gitianuser/.profile

Originally posted by @cevap in https://github.com/cevap/ion/issue_comments#issuecomment-445954818

I can confirm that this bug disappears when using qt 5.9.1

found that QT_XKB_CONFIG_ROOT can be any value as long as it's set

resolved by compiling on trusty, XKB fix is only required when we switch 100% to 5.9.x or higher. XKB fix works on rc7 and rc8.

missing qt fontbase etc errors were caused if pkg fails (as patch was not good), if patch is correct, then everything is fine.

I will close this as it is resolved for now, I will reopen this issue after we pull update_dependencies branch.


add SNLI / STS-2014 / Quora dataset

add SNLI dataset as mentioned in issue #146
add STS-2014 dataset
add Quora dataset.
@Victor0118 Could you please review this pr?

LGTM.


Web UI connecting only via LOCALHOST:5000, endpoint IP not working

Hello!
When i trying to connect to Web UI via internet to my direct white IP address with 5000 port i got error , only local web UI connection works

Same issue here. I tried to install and the deployment set it all up but there is something blocking the connection to tcp/5000 unless connecting to <IP_ADDRESS>:5000

By default wireguard-ui binds to the localhost address - which means you can't connect to it other than localhost. You can edit the startup script to bind to another address. Or, much better choice, configure a proxy server like nginx.


Bug: Markdown shortcuts for code are triggered ahead of time

The markdown shortcuts for code formating (``) and code block (```) get triggered "ahead-of-time", sort of. I don't recall observing this behaviour in earlier version of Lexical, but I haven't had the time to go back through each version to pinpoint which one introduced the bug, if any.
Lexical version: 0.8.0
Steps To Reproduce

Go to the playground and type any word(s) (i.e. any word(s) :laughing: ).
Wrap any of these words with a preceding accent grave character (`) and a succeeding one (a.k.a. the markdown shortcut for formating text as code). This can also be observed if you type three accent grave characters in a row (a.k.a. the markdown shortcut for a code block).

The current behavior
There's a leftover accent grave character after the transformation.
The expected behavior
There's no leftover accent grave characters after the transformation.

Just to be clear, by "ahead-of-time" I mean that the expected behaviour of an accent grave character is to become the diacritic of a composite unicode character (i.e. à), which means that the usual behaviour of text editors with such markdown transformations usually only register the character after the key for it is pressed twice for each position.
I recall this being the behaviour in Lexical as well but, as mentioned above, I started observing the new behaviour quite recently.

I don't think we've changed any of the Markdown logic recently, but this works as expected for myself. I'm using a Mac, so if I type OPTION + ~ then I see the accent grave character. I then type "a" and it gets transformed to "à".

But this wasn't about being able to type composite characters, @thegreatercurve  >.<. It's about the markdown shortcuts having an accent grave character as a leftover after the transformation for either the code format shortcut or the code block shortcut.

That's really weird indeed :S. I tested it in the playground with both Chrome and Firefox before redacting the bug :(.

Here's a recorded video:
https://watch.screencastify.com/v/O90sHrbX5LaOEZpziNyx

I have investigated a bit further, and this is what is known as a dead key.
I have tried to modify the regex to only match the unicode code point that represents the full character (U+0060), but it didn't work.
So far, the only work around is to modify my keyboard layout and set it to no dead keys, which is less than ideal... but it's something.
Maybe something could be done to prevent the transformation from happening if it's a composition key, @trueadm ?

Another possibility would be to not trigger the markdown transformers if the event is a dead key. Is it possible to access the keyboard event from the transformer functions?


require a gem client side gives a sprocket error

In my Gemfile I've got:
gem 'ruby-measurement'
but when requiring (require 'ruby-measurement') I've got this error:
Sprockets::FileNotFound at /
couldn't find file 'ruby-measurement' with type 'application/javascript'

I can require the gem in the task file with no problem. I'm doing something wrong? Sorry if this is an issue of Ruby instead of Volt.

@miguelalarcos you need to put the gem on the opal load path to require it on the client (for non-volt opal gems).  See here: http://docs.voltframework.com/en/getting_help/can_i_use_opal_gems.html  You can add something like: Opal.use_gem 'ruby-measurement' to your config/app.rb or one of your dependencies.rb file.

Good. But now I get:
RuntimeError: An error occurred while compiling: ruby-measurement/definitions/metric/length

Unexpected content in parsing stream `µm) ` :ruby-measurement/definitions/metric/length:11
Source: ruby-measurement/definitions/metric/length:11:19
  unit.convert_to(:µm) { |value| value * 10_000_000.0 }
~~~~~~~~~~~~~~~~~~^

But this is not Volt specific error. I'll investigate it. Thanks.


Improve lbry.tv static asset caching

Check all assets loaded by beta.lbry.tv to ensure they are cached and sized properly
At a minimum, favicon.ico and the font files are not being properly cached.
The font files should be continued to served from dynamic URLs with cache-control: public, max-age: <several months or a year in seconds>
The favicon should be checked for size/compression (168kb seems large) and served with cache-control: public, max-age: several days
The font files should be put directly in <head> and loaded with <link rel=preload>. See https://stackoverflow.com/questions/42616709/preloading-fonts-in-chrome-with-preload-link-directive

This was completed.


[shipping] reqwest spans taking a long duration

The reqwest spans part of the shippingservice take magnitudes longer duration than all other spans in a typical transaction that requires the shipping service

This seems to be related to #610, when reqwest with instrumentation was added, and #622 which also made changes to that instrumentation.
I expect HTTP requests from Rust to take microseconds, similar (or better) than other similar requests in the other languages in the demo.

Look to me the problem is the other side, at quoteservice:
root@shippinservice/# ./hey -m POST -c 1 -n 100 -d '{"numberOfItems":"5"}' http://quoteservice:8090/getquote

Summary:
  Total:        44.0418 secs
  Slowest:      0.6043 secs
  Fastest:      0.3200 secs
  Average:      0.4404 secs
  Requests/sec: 2.2706

  Total data:   400 bytes
  Size/request: 4 bytes

Response time histogram:
  0.320 [1]     |■■
  0.348 [4]     |■■■■■■■■
  0.377 [8]     |■■■■■■■■■■■■■■■
  0.405 [16]    |■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.434 [21]    |■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.462 [15]    |■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.491 [14]    |■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.519 [15]    |■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.547 [2]     |■■■■
  0.576 [0]     |
  0.604 [4]     |■■■■■■■■

Status code distribution:
  [200] 100 responses

Similar stats are when tested from load-generator service.

That's interesting. I see it locally, too. The traces themselves are reportedly quite fast (< 1ms, which I would expect), but the actual http request/response is painfully slow.
I do know that the runtime in use (apache + mod_php) does not complete & return the response until all processing has completed, and in this case that includes sending the telemetry data to the collector. I think that's the most likely cause, I'll do some debugging on it.

adding a sample xdebug profile if that helps
cachegrind.out.zip

Thanks @brettmc,  is the apache + mod_php combo technically prohibiting sending the telemetry data after the request is finished? Did a tcpdump test to believe ;)

My recollection (from a production outage caused by almost exactly this, with a different APM tool), is that the response to the user is not closed until all PHP processing is complete, which includes shutdown functions (which is where otel-php shuts down processors etc, and tries to export any un-exported data).
So I don't think it prohibits the sending of telemetry data, but rather delays the completion of the main response until telemetry data is done.
Most other PHP runtimes handle this much better, eg fastcgi and the more modern async runtimes.


desync with haxball

This sometimes happens. I will need to rewrite this from scratch soon so that there is no desync.

fixed all desync issues in the new version


fix(io): avoid blocking IO in callCli()

Fixes #117
I'm sure there's more than one way to skin this cat (use of ready(), NIO, etc.) though this solves the immediate problem and fits the current code style.
Ensure stderr doesn't starve waiting for stdout.

These changes look good to me. Thanks @codeplexity for jumping on this.

@axdotl @fabian-schlegel as two of the more active members, historically and in 2020, would one of you kindly comment on the process for review/merge/release? Thank you!

Hi there. I'm no longer with the company, means not able to do a merge or release.
Maybe @jekkel can jump in.

Hey @axdotl, I invited you as maintainer, that should restore your rights.


EFCore 6 release schedule

I like your project, very high code quality: the best EF batching addon I could find so far! I would love to use it in our e-commerce project Smartstore, where we currently rely on an inline fork of EFCore.BulkExtensions, but I'm not really happy with it (things gone mad after upgrading to EFCore 6 among other things).
Unfortunately I can't use your current packages because they are not compatible with our EFCore 6 stack (with MsSql & MySql support). When do you plan to release an update? I saw that you are working on EFCore 6 support.

My upgrade isn't fully tested. I will make a preview version later.

I have created a version 6.0.27-preview.
Please note that this extension doesn't have many common features with EFCore.BulkExtensions. You may still need to change a lot. :D

I'm not interested in bulk operations, but only batching. Is there anything concerning batch operations (especially delete and update) that your library lacks compared to EFCore.BulkExtensions?

You cannot update or delete with Skip/Take. However you can do some workaround like where id in (select …) to avoid this.
For other perspective I think it will be stronger than EFCore.BulkExtensions.

Thank you, works like a charm. Looking forward for stable release ;-)


php snippets broken because $$ doesn't properly escape $ under neovim vsnip

I have to change snippets that contain $$ to \\$ for it to work. Otherwise vsnip errors out and just prints the snippet up to the point $$ was used. The rest is truncated.
So given the following snippet
	"foreach …": {
		"prefix": "foreach",
		"body": [
			"foreach ($${1:variable} as $${2:key} ${3:=> $${4:value}}) {",
			"\t${0:# code...}",
			"}"
		],
		"description": "Foreach loop"
	}

only the following is printed
    foreach (
However when $ is escaped properly using \$ it works as expected.

Hey, I fixed the issue. Let my know if they work for you.

awesome!


dart2js: type inferrence misses methods in constants in some situations

I don't quite have a repro yet but I believe the important parts are:

A static const member that is defined as a const map from strings to functions, that refer to static methods of other classes
The only use of the constant is as a default value of an optional argument of an abstract class constructor
The only call to the above constructor is an implicit super constructor call in an instantiated class's constructor.

The static methods in the const map have arguments inferred as [empty].
I didn't get a repro before I had to leave for the day, but on the way home I realized #2 and/or #3 are probably why.

I believe this has been fixed, in the following program foo and bar show evidence of correct type inference
foo(x) {
  print(x + 33);
}

bar(x) {
  print(x + "42");
}

class A {
  A([x = const {'foo': foo, 'bar': bar}]) {
    x['foo'](9);
    return;
    return;
  }
}

class B extends A {
}

main() {
  new B();
}


assertNotThrown return value

assertNotThrown can call expressions that return data.
This allows the data to be returned from assertNotThrown.

LGTM

Other than that, LGTM. Thanks!!

added the Returns: block

LGTM, thanks for the quick response.

Auto-merge toggled on

thanks


Facing TypeError

Hi,
I am facing the below error,
TypeError: numpy boolean subtract, the - operator, is deprecated, use the bitwise_xor, the ^ operator, or the logical_xor function instead.
Please give some suggestion to solve this error.
Thanks in advance...

Hi! Can you. Could you indicate the cell and line of code where the error occurs?

Hi,
These are all the list of issues I get when i try to run the source.
Please give some suggestion to solve this error.
Thanks in advance...
Cell : Calculate the Histogram of Oriented Gradients¶
line 360 : fd_train[i], hog_image = hog(X_train_chars[i].reshape(28, 28), orientations=8, pixels_per_cell=(4, 4), cells_per_block=(1, 1), visualise=True)
File "/home/cd005/hulk/lib/python3.6/site-packages/skimage/feature/_hog.py", line 202, in hog
g_row, g_col = _hog_channel_gradient(image)
File "/home/cd005/hulk/lib/python3.6/site-packages/skimage/feature/_hog.py", line 38, in _hog_channel_gradient
g_row[1:-1, :] = channel[2:, :] - channel[:-2, :]
TypeError: numpy boolean subtract, the - operator, is deprecated, use the bitwise_xor, the ^ operator, or the logical_xor function instead.


Changes to the haproxy role to handle multiple environments

@siddharthvipul , @arrfab , @bstinsonmhk if you get a second to review please :)


Waiting for jasmine to end before going on

I have trouble figuring out how to wait for jasmine to be done. What I basically want to achieve is to have the tests be reported by Istanbul:
gulp.src('target/**/*Spec.js').pipe(jasmine()).pipe(istanbul.writeReports());
This does not work, as Instanbul starts writing reports while jasmine is still running. So I tried sequencing the tasks by introducing methods with callbacks like so:
function testAll(callback) {
	"use strict";
	gulp.src('target/**/*Spec.js')
		.pipe(jasmine())
		.on('end', callback);
}

My issue here is, when I use 'finish', the callback is invoked before jasmine is done. And wenn I use 'end', as suggested in another issue, the callback never gets invoked.
Any suggestion on what I am missing?
Thanks,
Stefan
Modules:
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>

Hi,
There's 2 parts to your question. The first is about Istanbul. I've used gulp-istanbul and gulp-jasmine together successfully using 2 patterns. The new one documented in their readme and the older one. Just replace mocha with jasmine and it should work correctly.
The second part is about the end event not firing. I'm unable to reproduce your problem. Here's what I used, with your exact npm versions:
gulpfile.js:
var gulp = require("gulp");
var jasmine = require("gulp-jasmine");

gulp.task("default", () =>
    gulp.src("test.spec.js")
        .pipe(jasmine())
        .on("end", () => {
            console.log("We're done!");
        })
);

test.spec.js:
describe("a test", () => {
    it("works", () => {
        expect(1).toBe(1);
    });
});

Hi,
Thanks for looking into it.
I re-tried the tests and reduced it to only using jasmine, no istanbul. Unfortunately, the end-Event does not get emitted, so there has to be some issue elsewhere in the system (maybe the node version itself).
Anyway, thanks again for your support.
Best regards,
Stefan

Hi,
I was able to reproduce the issue and found out that the 'end' event does not seem to be emitted when the stream is not returned. Not sure with your version of JS @jbblanchet, but maybe the stream is returned by default in your example.
When I return the stream, the 'end' event is emitted.
If I'm right - is this expected behaviour (return vs. no-return)?

@JaycobA: Got it! Thanks for taking the time to reproduce
You're right, when using a callback instead of returning the pipe it doesn't work. I must admit that I was a little stumped, and I still can't explain it, but I can rule out gulp-jasmine as the culprit. Try:
gulp.task("default", function (cb) {
    gulp.src("test.spec.js") // No gulp-jasmine
        .on("end", function () {
            console.log("We're done!");
            cb();
        });
});

and compare the behavior with:
gulp.task("default", function () {
    return gulp.src("test.spec.js") // No gulp-jasmine
        .on("end", function () {
            console.log("We're done!");
        });
});

OK, investigated the issue a little further, and it seems that the behaviour changed changed with version 3.8 of Gulp. Run your test with gulp 3.7, and it should work fine. Not sure why that is, I'll log a bug in the gulp repo.

Thanks for looking further into this issue. As going back to gulp 3.7 is no option, I tried using return, but it did not seem to help. What did help though, was adding a handler for the data event before the end handler. Although, the data event does nothing, the end event is emitted and the tests properly finish before going on.
So the code is now like:
function testAll(callback) {     "use strict";     gulp.src('target/**/*Spec.js')         .pipe(jasmine())         .on('data', () => {})         .on('end', callback); }

Just wanted to let you know that we're still working on a potential solution. If you want to understand why you need to add a data handler, have a look at #71.

Thanks @jbblanchet, I really appreciate your efforts in solving this.

Sorry about that, forgot to come back here and let you know how we resolved the situation. There was a lot of discussion about the best approach, but in the end we went with adding a new event to the pipeline, which is jasmineDone. So .on('jasmineDone', callback) should provide the behavior you were looking for.
This has been released in 2.4. I'll close the issue but feel free to discuss it here if there's still a problem.

Thank you @jbblanchet. I'll apply this as soon as we update to 2.4.


Migration $this->primaryKey()->unsigned() don't work for MySQL!

Showed error "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'UNSIGNED'".
Because it generated "id int(11) NOT NULL AUTO_INCREMENT PRIMARY KEY UNSIGNED" invalid sql.
Need correct sql like this "id int(11) unsigned NOT NULL AUTO_INCREMENT PRIMARY KEY".

+1
Oracle MySQL v5.7.11

primaryKey() uses schema pk type which is int(11) NOT NULL AUTO_INCREMENT PRIMARY KEY.

Same as 'id' => 'pk' in the old syntax.

So you think it's a wontfix?

I noticed some mistakes in my solutions:

We can't set the AUTO_INCREMENT attribute this ways. Only alterTable or SQL expression can help us here, I guess.
"PRIMARY" isn't good name for PRIMARY index. :) It may be blank string or any correct index name but not the "PRIMARY". Or else we'll receive an MySQL exception.
So, to my mind it's quite nice to set this attribute in some other way.

public function unsignedPrimaryKey();
public function unsignedBigPrimaryKey();

How about charPrimaryKey(), stringPrimaryKey()?

Maybe ColumnSchemaBuilder::autoIncrement()?
But in this case such method must define some index type.
Or could Yii replace schema parameters, if we extend it by unsigned() methods and so on? This is expected behavior of such methods, I guess.

@samdark It makes sense that pk()->unsigned() would produce a primary key as defined by Yii, but an unsigned version.
This is an argument about a virtual capacity. It doesn't really matter that we're throwing away half our "pool of resources" in this case. There is perhaps an OCD affection that drives one nuts tho, when you could access that "half" by the UNSIGNED modifier.

Its because the name of primaryKey() itself. Should be canged to another name like serial(), autoIncrement() or something else. Then primaryKey() use for real PRIMARY KEY.
'id' => $this->serial(), // <- int(11) NOT NULL AUTO_INCREMENT PRIMARY KEY

'coa' => $this->char(8)->primaryKey(), // <- char(8) PRIMARY KEY

[
    'order_id' => $this->integer()->notNull(),
    'product_id' => $this->integer()->notNull(),
    ...
    $this->primaryKey(['order_id','product_id']), // <- PRIMARY KEY ([[order_id]], [[product_id]])
]

Its because the name of primaryKey() itself. Should be canged to another name like serial(), autoIncrement() or something else. Then primaryKey() use for real PRIMARY KEY.

:+1:

See #10921 it's being fixed. Would you like to add to that @mdmunir . See the changes that have been made so far and how you would like to go ahead based on that.

Is this solved?

@pptyasar , yep.

Then how to create pk without Auto Increment

@pptyasar , currently (<=v2.0.10):
$this->createTable('tableName', [
    'id' => $this->integer()->unsigned()->notNull(),
    // ...
   'PRIMARY KEY ([[id]])',
]);

Or add primary key later, see Migration::addPrimaryKey()

@MysteryDragon

Or add primary key later, see Migration::addPrimaryKey()

This is how you do it:
$this->createTable('tableName', [
    'id' => $this->integer()->unsigned()->notNull(),
    // ...
]);
$this->addPrimaryKey('pk-id', 'tableName', 'id');

@Radon8472 if you seek some easy answer, it'll look like
$this->createTable('tableName', [
    // ...
    'field' => 'INT AUTO_INCREMENT NOT NULL',
]);

I mean you don't have to use schema builder 'cause it produces string at the end.
Same works for other statements like $this->addColumn(...), etc.
Or if you'd like to you can try to extend builder functionality.

@Radon8472 if you seek some easy answer, it'll look like
$this->createTable('tableName', [
    // ...
    'field' => 'INT AUTO_INCREMENT NOT NULL',
]);

I mean you don't have to use schema builder 'cause it produces string at the end. Same works for other statements like $this->addColumn(...), etc.
Or if you'd like to you can try to extend builder functionality.

Thank you.
I know, that I could write plain sql, but I try to learn how to work with the builder functions, like it was planned by the devs of yii .
But seems that there are some use cases that are hard to handle with the currently implemented methods.
My final solution what usses the builder as far as possible was:
$this->createTable('tableName', [
    'id' => $this->integer()->unsigned()->notNull()->append('AUTO_INCREMENT PRIMARY KEY'),
    // ...
]);

@Radon8472 that's true. Yii 2 isn't meant to be extremely flexible. It's more about simplicity + power together.
If you wanna do it "right way" then it's about implementing your own additional builder methods I believe.


Hadoop Versions lists hadoop-client twice in dependencies.

https://github.com/Netflix/PigPen/wiki/Hadoop-Versions:
git show 7c57e10                                                                                ⬆
Fri Sep 18 19:15:15 2015 -0500 7c57e10 (HEAD -> master) remove second instance of hadoop-client  [Randall Mason]
diff --git a/Hadoop Versions.md b/Hadoop Versions.md
index ade229c..89404c0 100644
--- a/Hadoop Versions.md
+++ b/Hadoop Versions.md
@@ -13,8 +13,7 @@ PigPen can also be used with Cloudera distributions of Hadoop. All you need to d
                  [com.netflix.pigpen/pigpen "0.3.0"]]
   :profiles {:dev {:dependencies
                    [[org.apache.hadoop/hadoop-client "2.0.0-mr1-cdh4.4.0"]
-                    [org.apache.pig/pig "0.11.0-cdh4.4.0"]
-                    [org.apache.hadoop/hadoop-client "2.0.0-mr1-cdh4.4.0"]]}})
+                    [org.apache.pig/pig "0.11.0-cdh4.4.0"]]}})
 ` ``

 This will prevent jar problems when the uberjar is submitted to the cluster.

Fixed. Thanks for the heads up!


Implement DPG core tests

Implement all testserver mentionned in https://github.com/Azure/autorest.testserver/wiki/Data-plane-codegen-testing in DPG testsuite.
Task is complete when there is a 100% for DPG testing in  http://azure.github.io/autorest/dashboard.html

Test server repo: https://github.com/azure/autorest.testserver

For developer-driven evolution, we'll need to resolve: https://github.com/Azure/autorest.csharp/issues/2014

https://github.com/azure/autorest.csharp/issues/1787 was originally tracking service driven evolution case.

We need to fix https://github.com/Azure/autorest.csharp/issues/2090.

Need to finish https://github.com/Azure/autorest.csharp/issues/2132

Reach to 100% coverage now.


Refactor protocol contracts

Clients are now called requesters. It was very weird how the entity making the request wasn't called a requester.
Requesters are now called sponsors. Designated wallets are called sponsor wallets, endorsing is called sponsoring. This both more literal and reduces the number of terms.
The request that refers to a template is now called a template request (instead of a client request/regular request)
Sponsors, requesters, airnodes are referred to as such, we don't say sponsorAddress, requesterAddress, airnodeAddress because these already type-d
Airnodes are now identified by the address of the default BIP 44 wallet derived from their mnemonic (instead of an ID).
Airnode gets its authorizers from config.json. authorizers on-chain is merely an announcement, like xpub. As a result:

We no longer have "default authorizers"
AirnodeRrp.sol is not Ownable, we don't have an OpenZeppelin dependency
Checking the authorization requires the caller to provide authorizer addresses as an argument

We still don't support authorizers with different interfaces
Sponsor wallet is no longer an authorizer argument (because we're hitting the stack limit by providing the authorizer addresses as an additional argument)

Entire protocol is reduced to three contracts

RequestUtils.sol implements the request functionality
WithdrawUtils.sol implements the withdrawal functionality
AirnodeRrp.sol inherits both of these and implements the convenience functions
Tests still run with the entire AirnodeRrp.sol

Improved tests, naming, in-code documentation for the protocol contracts
Removed redundant getter function in favor of calling the public variables directly (and added the public variables to the interfaces)

A change I forgot to mention: abi.encodePacked() is used to create the request IDs, so defaultAbiCoder.encode()s at the node-end will need to be replaced with solidityPack()


I met this problem.

I met this problem when i am recovering wallet on a different device. It is strange that some of my wallets can be recovered but some cannot. Anyone know this issue.

Did you check that all that things are correct when you import the wallet ? Re open the ticket if you still having issues. Thanks

@fjdkwangaa
I can recover your wallet if you want need help send me email<EMAIL_ADDRESS>


Cleanup inconsistent use of logging strings #2618 (Solved)

Hi. This is my first ever contribution, thanks for the opportunity. I have fixed the minor issues in relation to inconsistent use of logging strings. All logging functions used the correct format and was able to find only 1 extra mistake apart from the mentioned one in the issue. Thanks.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.psyvg1 seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.


Validating ResNet50

I am trying to validate the ResNet50 model which is supposed to give 92.9% Top5 Accuracy and 75.9% Top1 Accuracy (as mentioned: https://keras.io/applications/)
But I am getting only 88.3% Top5 Accuracy and 68.094% Top1 Accuracy.
I have no clue where I am going wrong. Can somebody please help?
The code is as following:
from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras.applications.resnet50 import preprocess_input, decode_predictions
import numpy as np
import glob
#Functions for top1 and top5 accuracies
def gettop1acc(predictions,truth):
counter=0
for i in range(len(predictions)):
if truth[i] == predictions[i]:
counter = counter+1
return counter*100/(np.size(predictions,axis=0))
def gettop5acc(predictions5,truth):
counter=0
for i in range(np.size(predictions5,axis=0)):
if truth[i] in predictions5[i][:]:
counter = counter+1
return counter*100/(np.size(predictions5,axis=0))
#model
rn = ResNet50(weights='imagenet')
#%%
#Read Data
path = '/hdd/rmk6217/ImageNet/ILSVRC2015/Data/CLS-LOC/val/'  #path to imagenet validation set images
X_names = np.array(glob.glob(path + "*.JPEG"))
X_names.sort()
noofinstances = len(X_names)
batchsize=500
#Batch sized X
X = np.zeros((batchsize,224,224,3),dtype=np.float32)
#Prediction for all images in the validation set
preds = np.zeros((noofinstances,1000),dtype=np.float32)
for i in range(0,int(noofinstances/batchsize)):
for j in range(0,batchsize):
img_path = X_names[j+(ibatchsize)]
img = image.load_img(img_path, target_size=(224, 224))
X[j] = image.img_to_array(img)
X = preprocess_input(X)
preds[ibatchsize:i*batchsize+batchsize,:] = rn.predict(X)
del X
#decode to get class, description and probability
p1all = decode_predictions(preds, top=1)
p5all = decode_predictions(preds, top=5)
#Get class for top 1
p1d =[]
for i in range(noofinstances):
p1d.append(p1all[i][0][0])
#Get class for top 5
p5d =[]
for i in range(noofinstances):
temp = []
for j in range(5):
temp.append(p5all[i][j][0])
p5d.append(temp)
#%%
path = '/hdd/rmk6217/ImageNet/ILSVRC2015/devkit/data/'   #path to dev-kit
#Load Ground Truth Labels
load = open(path+'ILSVRC2015_clsloc_validation_ground_truth.txt','r')
full = load.readlines()
gt = []
for i in range(len(full)):
temp = full[i].split()
gt.append(int(temp[0]))
#Load Mapping of Labels and Class
mapload = open(path+'map_clsloc.txt','r')
mapfull = mapload.readlines()
mapped = []
for i in range(len(mapfull)):
temp = mapfull[i].split()
mapped.append(temp[0])
#Map out the groundtruth in terms of classes
gtactual = []
for i in range(len(gt)):
temp = mapped[gt[i]-1]
gtactual.append(temp)
#Get top1 and top5 accuracy
print(gettop1acc(p1d,gtactual))
print(gettop5acc(p5d,gtactual))

Possible issues:

different image preprocessing
different validation set

Also try to see if you are getting the same results with the TF and Theano backends.
I believe the weights in the model can from He et al (ported from Caffe), so they should achieve the claimed accuracy.

If I use pixel wise mean instead of the pre-processing function given (https://keras.io/applications/), the top-5 accuracy goes to 89.88%. It doesn't even touch 90%.
The validation set for classification has been same since 2012. The images don't change. So its highly unlikely for the model to preform differently on the same set of images. [Also, coincidentally, I am using the same set as the paper i.e., 2015. So it actually shouldn't vary.]
I did try the two backends. The result is exactly the same.
If you can think of any other thing, please do let me know.
Quick question, did you not train ResNet50 for Keras ?

In fact, I have met the same problem, and I have tried many validation methods, and the top-n error is even lower than yours. It makes me confused. To my knowledge, the pretrained model weights are ported from others such as caffe and tensorflow. If you find the validation or train method that can get the close result, please let me know

I also have the same problem as @blarkj .
@fchollet : Since you did not actually to read @blarkj code, which already clearly shows that she used the preprocess_input designated for ResNet50 class (defined in imagenet_utils), I see no point in putting mine up. But the key points are as follows.

Used the 'imagenet' weights that Keras provides
Used the aptly named "preprocess_input" script for ResNet50 class. If this is not the processing to use, I don't know why it is named as such?
Used the same code that is available for Usage examples for image classification models which literally says "Classify ImageNet classes with ResNet50"
I don't think the validation images has changed. I used the 2012 version if that matters.
The Documentation for individual models claims 92.9 for resnet50, which is different from the reported number in the original paper (94.75 - 10 crop) as well different from the numbers reported in the caffe weights page (92.2% - single crop). It strongly suggests that the number found in Keras page is derived from some form of independent test done by someone, does it not?

We all just want to know what combination of preprocessing, cropping, and validation set gives the same number as claimed in Keras website? Could you provide or point towards a reproducible script that can get the same accuracy as reported in keras website or perhaps point to relevant pull request that does it. I could nowhere find anything about imagenet accuracy anywhere. If ResNet50 is meant to be used as off-the-shelf feature extractor, I think it is paramount that there exists a combination of preprocessing + code that can achieve the reported accuracy.

Lets see if we can bring this thread back to life..
I am facing the same problem as @blarkj  and @kushalkafle.
I am sure to use the correct ImageNet validation set and the "preprocess_input" method provided by Keras... it results in exactly the same accuracy: 88.3% Top5 and 68.1% Top1.
Also I cant reproduce the accuracies of the vgg16 and vgg19 nets provided in Keras (both significantly lower)!
@fchollet, there must be some script with which you confirmed the results on the Keras website.. it would be really helpful if you could provide this. Thanks in advance!

So what the Keras Applications page shows is that you can import the image resized to (224, 224) RGB and then preprocess the input i.e. subtract the spatial means and flip the image to BGR and then predict and you should get a pretty accurate estimate of the image.
However if you're evaluating the accuracy reported in the paper, the steps may be a tad bit different for preprocessing for validation:

Resize the image by converting the smaller edge to 256, i.e. if size of image is (500, 375), you resize it to (341, 256)

Now crop the center square of dimensions (224, 224) from the image

Flip the spatial dimensions to BGR if the image was loaded as RGB.

Now subtract the spatial mean image that was provided in Kaiming He's github repo. It is in .proto format so if you can convert to .npy it would be excellent, otherwise you can subtract the scalar means. As the image is BGR, subtract (103.939, 116.779, 123.68) from their respective channels.

Now when you validate the model, your Top-5 Accuracy should be around 92% and Top-1 as 74-75%

@sehgal-abhishek ,Thank you for your response, this problem makes me confused for a long time.

I'm experiencing the same issue for all the 13 pretrained networks and their respective accuracy (https://keras.io/applications/).
I do believe that Keras should elaborate in greater details on both the training and evaluating procedure in order to allow its users to replicate those results faithfully and make meaningful comparisons.
Although, I think this issue of not obtaining the exact validation accuracy is very important, but in my personal opinion, it's even more important to know the exact training procedure (including all the parameters set for the optimsier, number of epochs, image generation, etc.) to obtain "identical" weights (I understand due to the random nature of some of those procedures, once cant obtain identical weights, but close enough).
This way one can really compare the effect of changing one parameter on achieved accuracies. Otherwise, it will be always close to imposible to disentangle the importance of "architecture" versus "training procedure".
Thanks a lot :).

In the documentation, there is a section explaining for every model how the weights were obtained. What do you think is missing?

My bad, some are missing. You can find all the information here in the corresponding files: https://github.com/keras-team/keras-applications/tree/master/keras_applications

@gabrieldemarmiesse thank you for your prompt response.
Let's take ResNet50 as an example. In the documentation (https://keras.io/applications/#resnet50) it states: "These weights are ported from the ones released by Kaiming He under the MIT license."
In the GitHub of Kaiming He (https://github.com/KaimingHe/deep-residual-networks) there are two tables with different top-1 and top-5 accuracies, that neither of them correspond exactly to those of reported by Keras. So, confusion is already starting.
If we look at the article of Kaiming He (https://arxiv.org/pdf/1512.03385.pdf), section 3.4, it states "The standard color augmentation in [21] is used". At least to me, it's not clear what the standard augmentation is, whether is augmentation, or generation, etc. With respect to the optimiser, it doesn't state whether SGD has used Nesterov momentum or not.
In the source code itself (keras_applications/resnet50.py) there is no further information.
Naturally, you could object that I haven't investigated enough, which is fair enough. But, the point I'd like to make is that there has been a lot of efforts made to collect all these 13 pretrained networks. For sure they have been rigorously tested before publishing. Why not releasing the source code to exactly replicate those results. This facilitates the work of many researchers and avoids confusion.
This was an example, since the thread is about ResNet50. The same is true for most others. A quick another example, is mobilenet_v2. By
default the code points to this model (https://github.com/JonathanCMitchell/mobilenet_v2_keras/releases/download/v1.1/) . However, in the table of accuracy at the top of keras_applications/mobilenet_v2.py, there is no "v1.1".
I think these little things could make comparisons very difficult.
Thanks a lot :).

@ArashAkbarinia I just wrote up the steps I have found for reproducing the top-1/top-5 accuracy reported in the Keras documentation here, http://calebrob.com/ml/imagenet/ilsvrc2012/2018/10/22/imagenet-benchmarking.html. The code is here, https://github.com/calebrob6/imagenet_validation.
Let me know if this helps or if I can make the steps more clear!
Best.

Thanks @calebrob6 . I've tried the Keras "flow_from_directory" pipeline with the cropping @sehgal-abhishek  mentioned (similar to your code, however with inter linear interpolation rather than the cubic one), I could reproduce results closer to what the documentation of Keras states. However, for almost all as @RobinC94 mentioned there is tendency of 1-2% mismatch.

The difference between using linear and cubic interpolation is not large (I'm observing a 0.1% mismatch in top-5 accuracy). The most important steps seem to be the resizing method (the way @sehgal-abhishek described):

Resize the shorter side of each image to 256
Resize the longer side to maintain the aspect ratio
Central 224x224 crop

E.g. if we instead resize both edges of the validation images to 256x256 then take the central crop we get 1-2% mismatch.

So the pre-processing provided in my answer is only for ResNet and not for the other models in the applications list. I know Inception and MobileNet follow the same pre-processing as they were both developed at Google. But each of the models has their own pre-processing technique and Keras provides a pre-processing module built-in, though the document related to that is a bit sparse.
If you use a generic imagenet validation, it might not give you the exact accuracy as reported in the paper. Plus in the papers they also use an ensemble of models, and take multiple crops instead of the single center crop that I had done, which boosts the accuracy by 1-2%.

So what the Keras Applications page shows is that you can import the image resized to (224, 224) RGB and then preprocess the input i.e. subtract the spatial means and flip the image to BGR and then predict and you should get a pretty accurate estimate of the image.
However if you're evaluating the accuracy reported in the paper, the steps may be a tad bit different for preprocessing for validation:

Resize the image by converting the smaller edge to 256, i.e. if size of image is (500, 375), you resize it to (341, 256)
Now crop the center square of dimensions (224, 224) from the image
Flip the spatial dimensions to BGR if the image was loaded as RGB.
Now subtract the spatial mean image that was provided in Kaiming He's github repo. It is in .proto format so if you can convert to .npy it would be excellent, otherwise you can subtract the scalar means. As the image is BGR, subtract (103.939, 116.779, 123.68) from their respective channels.

Now when you validate the model, your Top-5 Accuracy should be around 92% and Top-1 as 74-75%

Thanks @sehgal-abhishek for your detailed answer. I have tried this code instead of calling Keras' ResNet preprocess_image function but for some reason the accuracy actually went down slightly:
        img_shape = image.shape
        # Resize the image by converting the smaller edge to 256
        smaller_edge = min(img_shape[0], img_shape[1])
        ratio = 256/smaller_edge
        img_shape = (int(img_shape[0] * ratio), int(img_shape[1] * ratio), img_shape[2])
        image = cv.resize(image, img_shape[0:2] )

        # Now crop the center square of dimensions (224, 224) from the image
        h, w, c = img_shape
        centre = (h//2, w//2)
        image = cv.getRectSubPix(image, (224,224), centre)

        # Flip the spatial dimensions to BGR if the image was loaded as RGB.
        image = np.flip(image, axis=-1)

        # Now subtract the spatial mean image that was provided in Kaiming He's github repo
        image = image - [103.939, 116.779, 123.68]

Hi @mostafaelhoushi  your code looks perfectly okay to me. The only things i can say is maybe you read the iage as BGR only and you may have not needed to change the shape.
Also I'm not properly familiar with the workings of cv.getRectSubPix.
@calebrob6 has provided a great imagenet validation notebook. You can compare with his code and see.
https://github.com/calebrob6/imagenet_validation/blob/master/1. Preprocess ImageNet validation set.ipynb
Let me know if it works out.

Many thanks to @calebrob6 ! Now I got almost the same accuracy as reported on keras.
Anyone managed to get the same validation accuracy for resnet50_v2? I noticed that the preprocessing is "tf" mode but still rescale and crop can also increase the accuracy. But the accuracy I got for resnet_v2 models are always around 5% lower compared to reported accuracy. Anyone tried on that?

I'm also noticing a difference in reported accuracy on ilsvrc2012 validation scores across models from what the current documentation reports. This is when using the sample inference code given there:
from tensorflow.keras.applications.resnet50 import ResNet50
from tensorflow.keras.preprocessing import image
from tensorflow.keras.applications.resnet50 import preprocess_input, decode_predictions
import numpy as np

model = ResNet50(weights='imagenet')

img_path = 'elephant.jpg'
img = image.load_img(img_path, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)

preds = model.predict(x)
# decode the results into a list of tuples (class, description, probability)
# (one such list for each sample in the batch)
print('Predicted:', decode_predictions(preds, top=3)[0])
# Predicted: [(u'n02504013', u'Indian_elephant', 0.82658225), (u'n01871265', u'tusker', 0.1122357), (u'n02504458', u'African_elephant', 0.061040461)]

I've verified that is not channel order, etc. Here's some of the difference's I'm seeing.

Model
Reported Top-1 Accuracy
Actual Top-1 Accuracy
Top-1 diff

DenseNet169
76.2%
73.7%
-2.5%

DenseNet201
77.3%
74.6%
-2.7%

InceptionV3
77.9%
76.4%
-1.5%

ResNet101
76.4%
68.6%
-7.8%

This seemed a bit surprising to me (and I'm still looking for a bug in my pipeline to explain this), but if I'm understanding this thread correctly the reported top-1 accuracy scores in the documentation are only attainable with a custom input pre-processing routine - so perhaps a drop is expected and having this reference table of actual accuracies with the given sample code is useful for others.

FYI... I totally gave up on getting the correct accuracy on Imagenet using Keras 2 years ago and had to switch to PyTorch. Their Imagenet script works out of the box: https://github.com/pytorch/examples/tree/master/imagenet


Highly scalable face clustering

Hey, first of all, thanks for your amazing work and written articles on these topics, they helped me out very much 👍
It seems like you focus a lot on face recognition (match 1 face to the k nearest neighbours), but maybe you have an idea on how to implement efficient face clustering(group faces together or split them apart on conflicting data).
My current stack consists of python and MongoDB, but I'm free to use any tool (currently trying Spark and ElasticSearch).
Since I want to cluster feature vectors without having all the vectors available (users upload new pictures), and I therefore can not know the total count of different clusters, k-means doesn't work. The only other algos for face clustering I have heard about are Chinese Whispers and DBSCAN, of which none are directly supported by Spark (and ElasticSearch doesn't support clustering at all since it just builds indexes as far as i know).
Also, just using Nearest Neighbour Search for each new photo and adding it to the cluster the nearest face is in also doesn't work, since clusters could only join this way, but couldn't split apart even if there would be new data which would indicate seperate clusters.
Maybe you have an idea for this problem, if not, or if this is out of scope for this project, feel free to just close this issue, since it's more a question than an issue.
Again, thanks for your work
Cheers 🎉

I just studied graph databases for this purpose. Here, you can find my experiments on neo4j.
Tutorial: https://sefiks.com/2021/04/03/deep-face-recognition-with-neo4j/
Video: https://youtu.be/X-hB2kBFBXs
Besides, instead of k-nn, have you ever try approximate nearest neighbors algorithm? Those are the popular a-nn libraries.
Spotify annoy: https://sefiks.com/2020/09/16/large-scale-face-recognition-with-spotify-annoy/
Facebook faiss: https://sefiks.com/2020/09/17/large-scale-face-recognition-with-facebook-faiss/
NMSLIB: https://sefiks.com/2020/09/19/large-scale-face-recognition-with-nmslib/
BTW, Elasticsearch wraps NMSLIB as well: https://sefiks.com/2020/11/27/large-scale-face-recognition-with-elasticsearch/

neo4j is absolutely amazing, I have never heard of a graph db! I will look into it later and see if this will work for my project as well. I am going to try Elasticsearch as well, since I need indecees for other things too (My Project uses OpenAI's Clip, and that produces Feature Vectors as well which need to be indexed). I think we can close this question for now, but maybe it would help other people if you could add the neo4j link to the readme, since clustering faces is usually a big usecase (there are many clustering related questions over a https://github.com/ageitgey/face_recognition)

neo4j appears in the read me of this repo actually.

I completely missed that, thanks for pointing it out 👍


Corss linking this performance test project with the storage readiness test project

Need to cross link this project with the storage readiness test project so users are ware of both projects and can run them as needed.
https://github.com/IBM/k8s-storage-perf
https://github.com/IBM/k8s-storage-tests

In this project, add the following at the beginning of the README:

Note that: if the tests in this storage readiness project are successful, you can perform further performance tests on the storage by following this companion project at https://github.com/IBM/k8s-storage-perf, and perform the tests provided there. It will give you a good assessment of the particular storage performance.

In the storage readiness project at https://github.com/IBM/k8s-storage-tests, added the following at the near beginning of the README:

Note that: if the tests in this storage readiness project are successful, you can perform further performance tests on the storage by following this companion project at https://github.com/IBM/k8s-storage-perf, and perform the tests provided there. It will give you a good assessment of the particular storage performance.

Please provide your comment/feedback. Close it for now.

minor change to the statements in the storage readiness README to below:

Note that: if the tests in this storage readiness project are successful, it's strongly recommended that you continue to perform further performance tests on the storage by following this companion project at https://github.com/IBM/k8s-storage-perf, and perform the tests provided there. It will give you a good assessment of the particular storage performance.