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[
"Same issue. https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android I tried too and failed with issue above.",
"Hi @perphyguo,\r\n\r\nPlease specify which Gradle version used for your project. Once change the `Android Gradle Plugin Version = 7.4.2` and `Gradle Version = 8.0` in your project structure and let us know the response.\r\n\r\nThank You",
"I'm on Mac (Sonoma 14.4.1, Android Studio Iguana | 2023.2.1 Patch 2\r\n) and get the same problem with \"gesture_classification), using AGP 7.2.0, Gradle 8.4.\r\n\r\n\r\nI've searched around for a couple of hours without making any progress, including trying to upgrade my gradle plugin, kotlin gradle plugin successfully to AGP 8.1.0 / 8.4 as per [this suggestion](https://discuss.gradle.org/t/could-not-create-task-compiledebugkotlin/46992/3), but that resulted in an additional compiler error, and I was also unable to complete the last step of running \"Tools -> AGP Upgrade Assistant\" (when I select the menu item, nothing happens). \r\n",
"Same Issue happens here also\r\nhttps://github.com/tensorflow/examples/tree/master/lite/examples/model_personalization/android",
"I faced same problem on https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android_java.\r\nModifying the gradle version from gradle-8.4 to gradle-7.4 solved the problem but I don‘t know why。\r\n\r\n ",
"Same problem (with gradle versions 8.4, and also the latest 8.7), also with `audio_classification`; same solution: downgrading to 7.4 fixed it. Using gradle from the command line (no Android Studio or plugin).",
"Hi @perphyguo ,\r\n\r\nI cloned the https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android and was able to build the project with the android with the \"Android Gradle Plugin version =72.1\" and \"gradle version = 7.3.3\" . Let me know if you have any further issues \r\n![Uploading Screenshot 2024-05-22 at 11.59.08 AM.png…]()\r\n",
"This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.",
"> I'm on Mac (Sonoma 14.4.1, Android Studio Iguana | 2023.2.1 Patch 2 ) and get the same problem with \"gesture_classification), using AGP 7.2.0, Gradle 8.4. \r\n> \r\n> I've searched around for a couple of hours without making any progress, including trying to upgrade my gradle plugin, kotlin gradle plugin successfully to AGP 8.1.0 / 8.4 as per [this suggestion](https://discuss.gradle.org/t/could-not-create-task-compiledebugkotlin/46992/3), but that resulted in an additional compiler error, and I was also unable to complete the last step of running \"Tools -> AGP Upgrade Assistant\" (when I select the menu item, nothing happens).\r\n\r\nI can build with this setup! Thank you~~~",
"Hi @perphyguo ,\r\n\r\nCan you please let me know if the provided solution worked for you?"
] | 2024-04-06T09:24:56 | 2024-06-11T14:35:14 | null |
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### Issue type
Build/Install
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
source
### TensorFlow version
donot know
### Custom code
No
### OS platform and distribution
windows 10
### Mobile device
_No response_
### Python version
_No response_
### Bazel version
_No response_
### GCC/compiler version
_No response_
### CUDA/cuDNN version
_No response_
### GPU model and memory
_No response_
### Current behavior?
I use android studio chipmunk to run several tflite examples. build failed
Here is the example I tried to run
https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android
FAILURE: Build failed with an exception.
* What went wrong:
Could not determine the dependencies of task ':app:packageDebug'.
> Could not create task ':app:mergeDebugAssets'.
> Cannot use @TaskAction annotation on method IncrementalTask.taskAction$gradle_core() because interface org.gradle.api.tasks.incremental.IncrementalTaskInputs is not a valid parameter to an action method.
I asked chatgpt, and tell me it should be gradle or apg version issue. I checked, the version should be fine.
I already change the jdk to java 11. so this is not problem
thanks
### Standalone code to reproduce the issue
```shell
FAILURE: Build failed with an exception.
* What went wrong:
Could not determine the dependencies of task ':app:packageDebug'.
> Could not create task ':app:mergeDebugAssets'.
> Cannot use @TaskAction annotation on method IncrementalTask.taskAction$gradle_core() because interface org.gradle.api.tasks.incremental.IncrementalTaskInputs is not a valid parameter to an action method.
* Try:
> Run with --info or --debug option to get more log output.
> Run with --scan to get full insights.
> Get more help at https://help.gradle.org.
* Exception is:
org.gradle.api.internal.tasks.TaskDependencyResolveException: Could not determine the dependencies of task ':app:packageDebug'.
at org.gradle.api.internal.tasks.CachingTaskDependencyResolveContext.getDependencies(CachingTaskDependencyResolveContext.java:68)
at org.gradle.execution.plan.TaskDependencyResolver.resolveDependenciesFor(TaskDependencyResolver.java:49)
at org.gradle.execution.plan.LocalTaskNode.getDependencies(LocalTaskNode.java:148)
at org.gradle.execution.plan.LocalTaskNode.resolveDependencies(LocalTaskNode.java:122)
at org.gradle.execution.plan.DefaultExecutionPlan.discoverNodeRelationships(DefaultExecutionPlan.java:184)
at org.gradle.execution.plan.DefaultExecutionPlan.doAddEntryNodes(DefaultExecutionPlan.java:156)
at org.gradle.execution.plan.DefaultExecutionPlan.addEntryTasks(DefaultExecutionPlan.java:131)
at org.gradle.execution.plan.DefaultExecutionPlan.addEntryTasks(DefaultExecutionPlan.java:123)
at org.gradle.execution.TaskNameResolvingBuildTaskScheduler.scheduleRequestedTasks(TaskNameResolvingBuildTaskScheduler.java:54)
at org.gradle.execution.DefaultTasksBuildTaskScheduler.scheduleRequestedTasks(DefaultTasksBuildTaskScheduler.java:72)
at org.gradle.initialization.DefaultTaskExecutionPreparer.lambda$scheduleRequestedTasks$0(DefaultTaskExecutionPreparer.java:46)
at org.gradle.internal.Factories$1.create(Factories.java:31)
at org.gradle.internal.work.DefaultWorkerLeaseService.withReplacedLocks(DefaultWorkerLeaseService.java:360)
at org.gradle.api.internal.project.DefaultProjectStateRegistry$DefaultBuildProjectRegistry.withMutableStateOfAllProjects(DefaultProjectStateRegistry.java:239)
at org.gradle.api.internal.project.DefaultProjectStateRegistry$DefaultBuildProjectRegistry.withMutableStateOfAllProjects(DefaultProjectStateRegistry.java:232)
at org.gradle.initialization.DefaultTaskExecutionPreparer.scheduleRequestedTasks(DefaultTaskExecutionPreparer.java:45)
at org.gradle.initialization.VintageBuildModelController.lambda$scheduleRequestedTasks$0(VintageBuildModelController.java:76)
at org.gradle.internal.model.StateTransitionController.lambda$inState$1(StateTransitionController.java:99)
at org.gradle.internal.model.StateTransitionController.lambda$inState$2(StateTransitionController.java:114)
at org.gradle.internal.work.DefaultSynchronizer.withLock(DefaultSynchronizer.java:44)
at org.gradle.internal.model.StateTransitionController.inState(StateTransitionController.java:110)
at org.gradle.internal.model.StateTransitionController.inState(StateTransitionController.java:98)
at org.gradle.initialization.VintageBuildModelController.scheduleRequestedTasks(VintageBuildModelController.java:76)
at org.gradle.internal.build.DefaultBuildLifecycleController$DefaultWorkGraphBuilder.addRequestedTasks(DefaultBuildLifecycleController.java:404)
at org.gradle.internal.buildtree.DefaultBuildTreeWorkPreparer.lambda$scheduleRequestedTasks$0(DefaultBuildTreeWorkPreparer.java:41)
at org.gradle.internal.build.DefaultBuildLifecycleController.lambda$populateWorkGraph$7(DefaultBuildLifecycleController.java:189)
at org.gradle.internal.build.DefaultBuildWorkPreparer.populateWorkGraph(DefaultBuildWorkPreparer.java:42)
at org.gradle.internal.build.BuildOperationFiringBuildWorkPreparer$PopulateWorkGraph.populateTaskGraph(BuildOperationFiringBuildWorkPreparer.java:106)
at org.gradle.internal.build.BuildOperationFiringBuildWorkPreparer$PopulateWorkGraph.run(BuildOperationFiringBuildWorkPreparer.java:92)
at org.gradle.internal.operations.DefaultBuildOperationRunner$1.execute(DefaultBuildOperationRunner.java:29)
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at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.run(DefaultBuildOperationRunner.java:47)
at org.gradle.internal.operations.DefaultBuildOperationExecutor.run(DefaultBuildOperationExecutor.java:73)
at org.gradle.internal.build.BuildOperationFiringBuildWorkPreparer.populateWorkGraph(BuildOperationFiringBuildWorkPreparer.java:67)
at org.gradle.internal.build.DefaultBuildLifecycleController.lambda$populateWorkGraph$8(DefaultBuildLifecycleController.java:189)
at org.gradle.internal.model.StateTransitionController.lambda$inState$1(StateTransitionController.java:99)
at org.gradle.internal.model.StateTransitionController.lambda$inState$2(StateTransitionController.java:114)
at org.gradle.internal.work.DefaultSynchronizer.withLock(DefaultSynchronizer.java:44)
at org.gradle.internal.model.StateTransitionController.inState(StateTransitionController.java:110)
at org.gradle.internal.model.StateTransitionController.inState(StateTransitionController.java:98)
at org.gradle.internal.build.DefaultBuildLifecycleController.populateWorkGraph(DefaultBuildLifecycleController.java:189)
at org.gradle.internal.build.DefaultBuildWorkGraphController$DefaultBuildWorkGraph.populateWorkGraph(DefaultBuildWorkGraphController.java:169)
at org.gradle.composite.internal.DefaultBuildController.populateWorkGraph(DefaultBuildController.java:76)
at org.gradle.composite.internal.DefaultIncludedBuildTaskGraph$DefaultBuildTreeWorkGraphBuilder.withWorkGraph(DefaultIncludedBuildTaskGraph.java:153)
at org.gradle.internal.buildtree.DefaultBuildTreeWorkPreparer.lambda$scheduleRequestedTasks$1(DefaultBuildTreeWorkPreparer.java:41)
at org.gradle.composite.internal.DefaultIncludedBuildTaskGraph$DefaultBuildTreeWorkGraph$1.run(DefaultIncludedBuildTaskGraph.java:209)
at org.gradle.internal.operations.DefaultBuildOperationRunner$1.execute(DefaultBuildOperationRunner.java:29)
at org.gradle.internal.operations.DefaultBuildOperationRunner$1.execute(DefaultBuildOperationRunner.java:26)
at org.gradle.internal.operations.DefaultBuildOperationRunner$2.execute(DefaultBuildOperationRunner.java:66)
at org.gradle.internal.operations.DefaultBuildOperationRunner$2.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:157)
at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.run(DefaultBuildOperationRunner.java:47)
at org.gradle.internal.operations.DefaultBuildOperationExecutor.run(DefaultBuildOperationExecutor.java:73)
at org.gradle.composite.internal.DefaultIncludedBuildTaskGraph$DefaultBuildTreeWorkGraph.scheduleWork(DefaultIncludedBuildTaskGraph.java:204)
at org.gradle.internal.buildtree.DefaultBuildTreeWorkPreparer.scheduleRequestedTasks(DefaultBuildTreeWorkPreparer.java:37)
at org.gradle.configurationcache.VintageBuildTreeWorkController$scheduleAndRunRequestedTasks$1.apply(VintageBuildTreeWorkController.kt:36)
at org.gradle.configurationcache.VintageBuildTreeWorkController$scheduleAndRunRequestedTasks$1.apply(VintageBuildTreeWorkController.kt:35)
at org.gradle.composite.internal.DefaultIncludedBuildTaskGraph.withNewWorkGraph(DefaultIncludedBuildTaskGraph.java:112)
at org.gradle.configurationcache.VintageBuildTreeWorkController.scheduleAndRunRequestedTasks(VintageBuildTreeWorkController.kt:35)
at org.gradle.internal.buildtree.DefaultBuildTreeLifecycleController.lambda$scheduleAndRunTasks$1(DefaultBuildTreeLifecycleController.java:68)
at org.gradle.internal.buildtree.DefaultBuildTreeLifecycleController.lambda$runBuild$4(DefaultBuildTreeLifecycleController.java:98)
at org.gradle.internal.model.StateTransitionController.lambda$transition$6(StateTransitionController.java:169)
at org.gradle.internal.model.StateTransitionController.doTransition(StateTransitionController.java:266)
at org.gradle.internal.model.StateTransitionController.lambda$transition$7(StateTransitionController.java:169)
at org.gradle.internal.work.DefaultSynchronizer.withLock(DefaultSynchronizer.java:44)
at org.gradle.internal.model.StateTransitionController.transition(StateTransitionController.java:169)
at org.gradle.internal.buildtree.DefaultBuildTreeLifecycleController.runBuild(DefaultBuildTreeLifecycleController.java:95)
at org.gradle.internal.buildtree.DefaultBuildTreeLifecycleController.scheduleAndRunTasks(DefaultBuildTreeLifecycleController.java:68)
at org.gradle.internal.buildtree.DefaultBuildTreeLifecycleController.scheduleAndRunTasks(DefaultBuildTreeLifecycleController.java:63)
at org.gradle.tooling.internal.provider.ExecuteBuildActionRunner.run(ExecuteBuildActionRunner.java:31)
at org.gradle.launcher.exec.ChainingBuildActionRunner.run(ChainingBuildActionRunner.java:35)
at org.gradle.internal.buildtree.ProblemReportingBuildActionRunner.run(ProblemReportingBuildActionRunner.java:49)
at org.gradle.launcher.exec.BuildOutcomeReportingBuildActionRunner.run(BuildOutcomeReportingBuildActionRunner.java:65)
at org.gradle.tooling.internal.provider.FileSystemWatchingBuildActionRunner.run(FileSystemWatchingBuildActionRunner.java:140)
at org.gradle.launcher.exec.BuildCompletionNotifyingBuildActionRunner.run(BuildCompletionNotifyingBuildActionRunner.java:41)
at org.gradle.launcher.exec.RootBuildLifecycleBuildActionExecutor.lambda$execute$0(RootBuildLifecycleBuildActionExecutor.java:40)
at org.gradle.composite.internal.DefaultRootBuildState.run(DefaultRootBuildState.java:123)
at org.gradle.launcher.exec.RootBuildLifecycleBuildActionExecutor.execute(RootBuildLifecycleBuildActionExecutor.java:40)
at org.gradle.internal.buildtree.InitDeprecationLoggingActionExecutor.execute(InitDeprecationLoggingActionExecutor.java:62)
at org.gradle.internal.buildtree.InitProblems.execute(InitProblems.java:38)
at org.gradle.internal.buildtree.DefaultBuildTreeContext.execute(DefaultBuildTreeContext.java:40)
at org.gradle.launcher.exec.BuildTreeLifecycleBuildActionExecutor.lambda$execute$0(BuildTreeLifecycleBuildActionExecutor.java:65)
at org.gradle.internal.buildtree.BuildTreeState.run(BuildTreeState.java:58)
at org.gradle.launcher.exec.BuildTreeLifecycleBuildActionExecutor.execute(BuildTreeLifecycleBuildActionExecutor.java:65)
at org.gradle.launcher.exec.RunAsBuildOperationBuildActionExecutor$3.call(RunAsBuildOperationBuildActionExecutor.java:61)
at org.gradle.launcher.exec.RunAsBuildOperationBuildActionExecutor$3.call(RunAsBuildOperationBuildActionExecutor.java:57)
at org.gradle.internal.operations.DefaultBuildOperationRunner$CallableBuildOperationWorker.execute(DefaultBuildOperationRunner.java:204)
at org.gradle.internal.operations.DefaultBuildOperationRunner$CallableBuildOperationWorker.execute(DefaultBuildOperationRunner.java:199)
at org.gradle.internal.operations.DefaultBuildOperationRunner$2.execute(DefaultBuildOperationRunner.java:66)
at org.gradle.internal.operations.DefaultBuildOperationRunner$2.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:157)
at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.call(DefaultBuildOperationRunner.java:53)
at org.gradle.internal.operations.DefaultBuildOperationExecutor.call(DefaultBuildOperationExecutor.java:78)
at org.gradle.launcher.exec.RunAsBuildOperationBuildActionExecutor.execute(RunAsBuildOperationBuildActionExecutor.java:57)
at org.gradle.launcher.exec.RunAsWorkerThreadBuildActionExecutor.lambda$execute$0(RunAsWorkerThreadBuildActionExecutor.java:36)
at org.gradle.internal.work.DefaultWorkerLeaseService.withLocks(DefaultWorkerLeaseService.java:264)
at org.gradle.internal.work.DefaultWorkerLeaseService.runAsWorkerThread(DefaultWorkerLeaseService.java:128)
at org.gradle.launcher.exec.RunAsWorkerThreadBuildActionExecutor.execute(RunAsWorkerThreadBuildActionExecutor.java:36)
at org.gradle.tooling.internal.provider.continuous.ContinuousBuildActionExecutor.execute(ContinuousBuildActionExecutor.java:110)
at org.gradle.tooling.internal.provider.SubscribableBuildActionExecutor.execute(SubscribableBuildActionExecutor.java:64)
at org.gradle.internal.session.DefaultBuildSessionContext.execute(DefaultBuildSessionContext.java:46)
at org.gradle.tooling.internal.provider.BuildSessionLifecycleBuildActionExecuter$ActionImpl.apply(BuildSessionLifecycleBuildActionExecuter.java:92)
at org.gradle.tooling.internal.provider.BuildSessionLifecycleBuildActionExecuter$ActionImpl.apply(BuildSessionLifecycleBuildActionExecuter.java:80)
at org.gradle.internal.session.BuildSessionState.run(BuildSessionState.java:69)
at org.gradle.tooling.internal.provider.BuildSessionLifecycleBuildActionExecuter.execute(BuildSessionLifecycleBuildActionExecuter.java:62)
at org.gradle.tooling.internal.provider.BuildSessionLifecycleBuildActionExecuter.execute(BuildSessionLifecycleBuildActionExecuter.java:41)
at org.gradle.tooling.internal.provider.StartParamsValidatingActionExecuter.execute(StartParamsValidatingActionExecuter.java:64)
at org.gradle.tooling.internal.provider.StartParamsValidatingActionExecuter.execute(StartParamsValidatingActionExecuter.java:32)
at org.gradle.tooling.internal.provider.SessionFailureReportingActionExecuter.execute(SessionFailureReportingActionExecuter.java:51)
at org.gradle.tooling.internal.provider.SessionFailureReportingActionExecuter.execute(SessionFailureReportingActionExecuter.java:39)
at org.gradle.tooling.internal.provider.SetupLoggingActionExecuter.execute(SetupLoggingActionExecuter.java:47)
at org.gradle.tooling.internal.provider.SetupLoggingActionExecuter.execute(SetupLoggingActionExecuter.java:31)
at org.gradle.launcher.daemon.server.exec.ExecuteBuild.doBuild(ExecuteBuild.java:65)
at org.gradle.launcher.daemon.server.exec.BuildCommandOnly.execute(BuildCommandOnly.java:37)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.WatchForDisconnection.execute(WatchForDisconnection.java:39)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.ResetDeprecationLogger.execute(ResetDeprecationLogger.java:29)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.RequestStopIfSingleUsedDaemon.execute(RequestStopIfSingleUsedDaemon.java:35)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.ForwardClientInput$2.create(ForwardClientInput.java:78)
at org.gradle.launcher.daemon.server.exec.ForwardClientInput$2.create(ForwardClientInput.java:75)
at org.gradle.util.internal.Swapper.swap(Swapper.java:38)
at org.gradle.launcher.daemon.server.exec.ForwardClientInput.execute(ForwardClientInput.java:75)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.LogAndCheckHealth.execute(LogAndCheckHealth.java:64)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.LogToClient.doBuild(LogToClient.java:63)
at org.gradle.launcher.daemon.server.exec.BuildCommandOnly.execute(BuildCommandOnly.java:37)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.EstablishBuildEnvironment.doBuild(EstablishBuildEnvironment.java:84)
at org.gradle.launcher.daemon.server.exec.BuildCommandOnly.execute(BuildCommandOnly.java:37)
at org.gradle.launcher.daemon.server.api.DaemonCommandExecution.proceed(DaemonCommandExecution.java:104)
at org.gradle.launcher.daemon.server.exec.StartBuildOrRespondWithBusy$1.run(StartBuildOrRespondWithBusy.java:52)
at org.gradle.launcher.daemon.server.DaemonStateCoordinator$1.run(DaemonStateCoordinator.java:297)
at org.gradle.internal.concurrent.ExecutorPolicy$CatchAndRecordFailures.onExecute(ExecutorPolicy.java:64)
at org.gradle.internal.concurrent.AbstractManagedExecutor$1.run(AbstractManagedExecutor.java:47)
Caused by: org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreationException: Could not create task ':app:mergeDebugAssets'.
at org.gradle.api.internal.tasks.DefaultTaskContainer.taskCreationException(DefaultTaskContainer.java:721)
at org.gradle.api.internal.tasks.DefaultTaskContainer.access$600(DefaultTaskContainer.java:77)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider.domainObjectCreationException(DefaultTaskContainer.java:713)
at org.gradle.api.internal.DefaultNamedDomainObjectCollection$AbstractDomainObjectCreatingProvider.tryCreate(DefaultNamedDomainObjectCollection.java:954)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider.access$1401(DefaultTaskContainer.java:660)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider$1.run(DefaultTaskContainer.java:686)
at org.gradle.internal.operations.DefaultBuildOperationRunner$1.execute(DefaultBuildOperationRunner.java:29)
at org.gradle.internal.operations.DefaultBuildOperationRunner$1.execute(DefaultBuildOperationRunner.java:26)
at org.gradle.internal.operations.DefaultBuildOperationRunner$2.execute(DefaultBuildOperationRunner.java:66)
at org.gradle.internal.operations.DefaultBuildOperationRunner$2.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:157)
at org.gradle.internal.operations.DefaultBuildOperationRunner.execute(DefaultBuildOperationRunner.java:59)
at org.gradle.internal.operations.DefaultBuildOperationRunner.run(DefaultBuildOperationRunner.java:47)
at org.gradle.internal.operations.DefaultBuildOperationExecutor.run(DefaultBuildOperationExecutor.java:73)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider.tryCreate(DefaultTaskContainer.java:682)
at org.gradle.api.internal.DefaultNamedDomainObjectCollection$AbstractDomainObjectCreatingProvider.calculateOwnValue(DefaultNamedDomainObjectCollection.java:935)
at org.gradle.api.internal.provider.AbstractMinimalProvider.calculateOwnPresentValue(AbstractMinimalProvider.java:80)
at org.gradle.api.internal.provider.AbstractMinimalProvider.get(AbstractMinimalProvider.java:100)
at org.gradle.api.internal.DefaultNamedDomainObjectCollection$AbstractDomainObjectCreatingProvider.get(DefaultNamedDomainObjectCollection.java:921)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider.getProducer(DefaultTaskContainer.java:677)
at org.gradle.api.internal.tasks.DefaultTaskDependency.visitDependencies(DefaultTaskDependency.java:104)
at org.gradle.api.internal.tasks.CachingTaskDependencyResolveContext$TaskGraphImpl.getNodeValues(CachingTaskDependencyResolveContext.java:103)
at org.gradle.internal.graph.CachingDirectedGraphWalker$GraphWithEmptyEdges.getNodeValues(CachingDirectedGraphWalker.java:213)
at org.gradle.internal.graph.CachingDirectedGraphWalker.doSearch(CachingDirectedGraphWalker.java:121)
at org.gradle.internal.graph.CachingDirectedGraphWalker.findValues(CachingDirectedGraphWalker.java:73)
at org.gradle.api.internal.tasks.CachingTaskDependencyResolveContext.getDependencies(CachingTaskDependencyResolveContext.java:66)
... 143 more
Caused by: org.gradle.api.GradleException: Cannot use @TaskAction annotation on method IncrementalTask.taskAction$gradle_core() because interface org.gradle.api.tasks.incremental.IncrementalTaskInputs is not a valid parameter to an
action method.
at org.gradle.api.internal.project.taskfactory.DefaultTaskClassInfoStore.createTaskAction(DefaultTaskClassInfoStore.java:126)
at org.gradle.api.internal.project.taskfactory.DefaultTaskClassInfoStore.createTaskClassInfo(DefaultTaskClassInfoStore.java:63)
at org.gradle.api.internal.project.taskfactory.DefaultTaskClassInfoStore.lambda$new$0(DefaultTaskClassInfoStore.java:43)
at org.gradle.cache.internal.DefaultCrossBuildInMemoryCacheFactory$AbstractCrossBuildInMemoryCache.get(DefaultCrossBuildInMemoryCacheFactory.java:130)
at org.gradle.api.internal.project.taskfactory.DefaultTaskClassInfoStore.getTaskClassInfo(DefaultTaskClassInfoStore.java:51)
at org.gradle.api.internal.project.taskfactory.AnnotationProcessingTaskFactory.process(AnnotationProcessingTaskFactory.java:52)
at org.gradle.api.internal.project.taskfactory.AnnotationProcessingTaskFactory.create(AnnotationProcessingTaskFactory.java:48)
at org.gradle.api.internal.tasks.DefaultTaskContainer.createTask(DefaultTaskContainer.java:328)
at org.gradle.api.internal.tasks.DefaultTaskContainer.access$200(DefaultTaskContainer.java:77)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider.createDomainObject(DefaultTaskContainer.java:703)
at org.gradle.api.internal.tasks.DefaultTaskContainer$TaskCreatingProvider.createDomainObject(DefaultTaskContainer.java:660)
at org.gradle.api.internal.DefaultNamedDomainObjectCollection$AbstractDomainObjectCreatingProvider.tryCreate(DefaultNamedDomainObjectCollection.java:947)
... 165 more
```
### Relevant log output
_No response_
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Redefines the identifier API of the kind of a `PjRtMemorySpace`:
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Redefines the identifier API of the kind of a `PjRtMemorySpace`:
1) `PjRtMemorySpace::kind()` returns a verbose string identifying the kind of a `PjRtMemorySpace` instance. For instance, "device", "pinned_host".
2) `PjRtMemorySpace::kind_id()` returns a unique ID identifying the kind ID of a `PjRtMemorySpace` instance. This is useful for quickly comparing the kinds of memory spaces.
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Automated Code Change
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[tsl:concurrency] Add LLVM-style type casting to AsyncValuePtr<T>
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[tsl:concurrency] Add LLVM-style type casting to AsyncValuePtr<T>
AsyncValueRef<T> type casting coming in followup CL, it will be a bit more tricky because it's not clear when to return a ref-copy and when to return a non-owning AsyncValuePtr.
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PR_kwDOArmXAs5r5pHO
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IfrtServingExecutable support host callback execution
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PR_kwDOArmXAs5r5lwN
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Removes useless friend declaration.
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Removes useless friend declaration.
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Support non-descending layout for SparseCore fusion.
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Support non-descending layout for SparseCore fusion.
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[XLA:MSA] Add option to filter buffers by size in bytes to override their priority of alternate memory assignment.
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[XLA:MSA] Add option to filter buffers by size in bytes to override their priority of alternate memory assignment.
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Reverts 664bac882e57fa04900870162c04cbd3db853d1d
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Reverts 664bac882e57fa04900870162c04cbd3db853d1d
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Allow both nb::tuple and nb::list for fastpath_data.
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Allow both nb::tuple and nb::list for fastpath_data.
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PR_kwDOArmXAs5r5IZB
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Use StreamExecutor to create stream rather than manually constructing.
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Use StreamExecutor to create stream rather than manually constructing.
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PR_kwDOArmXAs5r5Hum
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Enforce that CLs satisfy openxla/xla's buildifier checks
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PR_kwDOArmXAs5r5Asu
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Add `Layout` support to `jax.jit`.
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Add `Layout` support to `jax.jit`.
`jax.jit` now accepts `Layout` instances to the `in_shardings` and `out_shardings` argument. Major changes are just plumbing `in_layouts` and `out_layouts` everywhere.
Note that public api is `Layout(device_local_layout, sharding)` which is how users will pass us the Layout but internally we split them apart into device_local_layout and sharding.
Docs are coming up on how to use the API and what Layouts mean and how to make sense of them (especially on TPU).
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PR_kwDOArmXAs5r5ALM
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Update comments per TODOs.
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Update comments per TODOs.
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Model.add_loss is not documented
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[
"@piyushsrv The Model page doesn't explicitly mention add_loss, you can still use it on a Model object because it inherits from Layer. Model inherits from Layer in Keras. This means it gets all the methods and properties of the Layer by default. You can refer to the Layer.add_loss documentation for details on how it works: https://www.tensorflow.org/api_docs/python/tf/keras/losses.\r\nThank you!",
"This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.",
"This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further.",
"Are you satisfied with the resolution of your issue?\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/65160\">Yes</a>\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/65160\">No</a>\n"
] | 2024-04-05T22:04:08 | 2024-04-25T01:48:35 | 2024-04-25T01:48:31 |
NONE
| null | null | null |
### Issue type
Documentation Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
binary
### TensorFlow version
2.16.1
### Custom code
Yes
### OS platform and distribution
_No response_
### Mobile device
_No response_
### Python version
_No response_
### Bazel version
_No response_
### GCC/compiler version
_No response_
### CUDA/cuDNN version
_No response_
### GPU model and memory
_No response_
### Current behavior?
In the documentation of `tf.keras.Model` as available at https://www.tensorflow.org/api_docs/python/tf/keras/Model, the method `Model.add_loss` has been used in the example code for the method `compute_loss`. However, the method `Model.add_loss` itself has not been documented on this page.
The `keras` documentation provides some documentation for `Layer.add_loss`, but I couldn't find any documentation even there for `Model.add_loss`.
### Standalone code to reproduce the issue
```shell
This is a missing documentation issue, so there is no code.
```
### Relevant log output
_No response_
|
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HloTopKInstruction doesn't inherit from HloDimensionsInstruction,
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HloTopKInstruction doesn't inherit from HloDimensionsInstruction,
HloDimensionsInstruction::ClassOf should return false for kTopK.
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Add e2e tests for TF models with function alias.
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Add e2e tests for TF models with function alias.
In addition to tf.StatefulPartitionedCall, some aliased functions are lowered as tf.PartitionedCall. We preserve (Stateful)ParittionedCall ops to preserve aliases. This CL completes the handling of such cases and added some test cases.
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[PJRT C API] Add a build rule for building the PJRT CPU plugin.
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[PJRT C API] Add a build rule for building the PJRT CPU plugin.
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XProf GPU: Using Per-Thread callback api data for CUPTI collector for better overhead. Move per-thread control to CuptiTracerBEGIN_PUBLIC
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XProf GPU: Using Per-Thread callback api data for CUPTI collector for better overhead. Move per-thread control to CuptiTracerBEGIN_PUBLIC
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Defines a solver 'output' class, to replace the earlier (unnamed) tuple.
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NONE
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#tf-data copies is_legacy_prefetch_autotuned_ when snapshotting
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#tf-data copies is_legacy_prefetch_autotuned_ when snapshotting
Reverts e664ade8a0063f2800f27df3e4c96358e376c5cf
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[IFRT] Add fast pointer equality test for `DeviceList` internal state
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[IFRT] Add fast pointer equality test for `DeviceList` internal state
Copied `DeviceList`s share their internal state with the source `DeviceList`.
We leverage it to make comparison faster between two `DeviceList` that are a
(transitive) copy of the other.
The single-device `DeviceList` does not use pointer equality test because the
internal state is not wrapped in a shared pointer, but this case will not
benefit from pointer equality test anyway.
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[IFRT] Cache the hash of `DeviceList`
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[IFRT] Cache the hash of `DeviceList`
This change makes `xla::ifrt::DeviceList` cache its hash value once it is
computed. This makes it fast to compare two `DeviceList`s if they are created
from two different sources.
This is a part of the change that will enable the user of `DeviceList` build their
own cache to store runtime-specific attributes for the devices.
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Breaks TF MacOS arm64 (min/max python) and Linux min_python Kokoro tests
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Breaks TF MacOS arm64 (min/max python) and Linux min_python Kokoro tests
Reverts cd3b38bfb0215e65d765dd766dad8e98068759db
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Fix a bug in algebraic simplifier that incorrectly rewrites a broadcast to transpose.
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Fix a bug in algebraic simplifier that incorrectly rewrites a broadcast to transpose.
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Add sycl build target #10244
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Add sycl build target #10244
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Remove usages of bridge fallback.
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Automated Code Change
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TFLite: cyclic dependency error Tflite simple opaque delegate
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[
"Hi @suyash-narain,\r\nAs per my knowledge, the error you are encountering is a classic cyclic dependency issue when building the TensorFlow Lite library. First try the following commands to resolve the cyclic dependency.\r\n``` git submodule foreach git clean -dfx```\r\n``` git submodule update``` and \r\ninstead of including `simple_opaque_delegate` directly in `libtensorflowlite.so`, try to build it as a separate static library. This library can then be linked with applications that need the delegate functionality, without requiring it to be part of the core TensorFlow Lite library. \r\nHave you tried with latest TF 2.16.1 stable version?. If not resolved with this, please help us with reproducible code to resolve the issue.\r\nThank You\r\n\r\n",
"This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.",
"This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further.",
"Are you satisfied with the resolution of your issue?\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/65146\">Yes</a>\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/65146\">No</a>\n"
] | 2024-04-05T19:36:35 | 2024-04-27T01:47:28 | 2024-04-27T01:47:25 |
NONE
| null | null | null |
I am using tf v2.14 and would like to build tflite opaque delegate such that its references are included in the tflite shared library libtensorflowlite.so
when i include simple_opaque_delegate build targets in the tflite BUILD file //tensorflow/lite/BUILD, I get the cyclic dependency error:
```
ERROR: /tensorflow/tensorflow/lite/BUILD:479:23: in cc_library rule //tensorflow/lite:framework_stable: cycle in dependency graph:
//tensorflow/lite:libtensorflowlite.so (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
//tensorflow/lite/kernels:builtin_ops_all_linked (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
.-> //tensorflow/lite:framework_stable (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite:cc_api_stable (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/delegates/external:external_delegate (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/delegates/utils:simple_opaque_delegate (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/c:c_api_experimental (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/c:c_api (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/core/c:c_api (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite:create_op_resolver_with_builtin_ops (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/core:create_op_resolver_with_builtin_ops (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/core/kernels:builtin_ops (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/kernels:builtin_op_kernels (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
| //tensorflow/lite/kernels:variable_op_kernels (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
`-- //tensorflow/lite:framework_stable (adc6a2edc02c0f50690f56ac867f112f9172c147f91c4ef0c8b89d477f7c8720)
ERROR: analysis of target '//tensorflow/lite:libtensorflowlite.so' failed; build aborted
```
I add the build target below this line: https://github.com/tensorflow/tensorflow/blob/50d63587561074139dba4053c8023d5ea8fd6cf7/tensorflow/lite/BUILD#L750
adding it as a dep to build the tensorflowlite shared library //tensorflow/lite/delegates/utils:simple_opaque_delegate
how do i ensure simple_opaque_delegate is built and its symbols present in the tensorflowlite shared library?
If i replace simple_opaque_delegate with simple_delegate, i don't get this error though and shared library builds perfectly.
thanks
|
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Previous fix only works when there is a transpose copy. The mechanism should
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Previous fix only works when there is a transpose copy. The mechanism should
work regardless of the existence of such copies. Also add some filtering for a special case where at loop entry a tensor is on the host, for which case the root instruction of the loop body should not use the moved-to-device version.
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Fix Copybara reversibility issues
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[XLA:Runtime] Moved the nccl_clique_key target to runtime folder.
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[XLA:Runtime] Moved the nccl_clique_key target to runtime folder.
This is part of an effort to move runtime targets to the runtime folder. #5758
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[XLA:GPU] Compute a graph of TiledHloInstruction for given tile parameters.
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[XLA:GPU] Compute a graph of TiledHloInstruction for given tile parameters.
Use TiledHloInstructions in the Triton emitter.
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Add GetDefaultLayoutForDevice to IFRT.
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Add GetDefaultLayoutForDevice to IFRT.
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Adding support for transpose to LayoutCanonicalizer pass.
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Adding support for transpose to LayoutCanonicalizer pass.
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Integrate LLVM at llvm/llvm-project@8487e05967aa
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Integrate LLVM at llvm/llvm-project@8487e05967aa
Updates LLVM usage to match
[8487e05967aa](https://github.com/llvm/llvm-project/commit/8487e05967aa)
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#shlo_ref Fix I4 tests.
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#shlo_ref Fix I4 tests.
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Fix Copybara reversibility issues
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Fix Copybara reversibility issues
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#shlo_ref Add F16 wrapper type
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#shlo_ref Add F16 wrapper type
_Float16 is not available on the GCC until version 13, which is very recent. This change transforms the F16 into a wrapper type that will always be used regardless of compiler support. It defines conversion and arithmetic operators. If _Float16 is available, that will be used as the underlying type. If it is not, we'll use a uint16_t bits format and the FP16 library for converting between float and uint16_t.
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#shlo_ref Rework quantized tensor element types.
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#shlo_ref Rework quantized tensor element types.
This separates the implementation of per-tensor and per-axis quantization
types. The goal is to allow value parametrized tests without having to use
templating mechanisms to create the values. This will also make the user
dispatching code much more concise.
- Information duplication is reduced in the quantized type structures (only the variants).
- The code is better decoupled.
- Per-tensor does not need to get the per axis 0th element for scales and zero points.
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Prepare move of CUDA compilation functionality
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NONE
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Prepare move of CUDA compilation functionality
Currently PTX to SASS compilation functions are exported by the target `stream_executor/gpu:asm_compiler`, but implemented in `stream_executor/cuda:cuda_asm_compiler`.
I'm trying to clean this up by moving everything into `:cuda_asm_compiler`. Since we can't do atomic cross cutting changes between Jaxlib and XLA, I'm only preparing `:cuda_asm_compiler` as an alias for Jaxlib to depend on.
In a subsequent change I will move all the code over.
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Add the priority_isolation policy to the BatchFunction op to disallow mixing the high priority and low priority tasks
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Add the priority_isolation policy to the BatchFunction op to disallow mixing the high priority and low priority tasks
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Fix HLO cost analysis for simple nested fusions.
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Fix HLO cost analysis for simple nested fusions.
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Remove unused proto imports
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Remove unused proto imports
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| 65,129 |
Lazily instantiates memory constraints.
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NONE
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Lazily instantiates memory constraints.
Reverts af4e1d5038bfb576d3fcc775962d764dccdc2d93
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Rolling back for now.
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NONE
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Rolling back for now.
Reverts af4e1d5038bfb576d3fcc775962d764dccdc2d93
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Adds utilities for extracting chosen node & edge strategies.
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NONE
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Adds utilities for extracting chosen node & edge strategies.
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Automated Code Change
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NONE
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Automated Code Change
Reverts af4e1d5038bfb576d3fcc775962d764dccdc2d93
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Several typos are fixed and reframed the sentence
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Fix test to load autotuning results from cache instead of actually computing it. This test wants to assume CUBLAS is always faster than Triton for this particular GEMM, and can only be so via autotuning DB.
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Fix test to load autotuning results from cache instead of actually computing it. This test wants to assume CUBLAS is always faster than Triton for this particular GEMM, and can only be so via autotuning DB.
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Move CUDA specific functions from asm_compiler to cuda_asm_compiler target
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Move CUDA specific functions from asm_compiler to cuda_asm_compiler target
This avoids:
- a forward declaration of `GpuContext`
- the `:asm_compiler_header` header only target
The moved code is unchanged - I just move it from one
file to another and fix up includes and dependencies.
Note that this is adding just another `#ifdef` to the redzone allocator code. I will clean this up in a subsequent change.
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PR_kwDOArmXAs5r2mqi
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Move LoadKernelOrGetPtr into :redzone_allocator
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Move LoadKernelOrGetPtr into :redzone_allocator
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After this change `asm_compiler.h` and its target does
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Note that this adds another `if GOOGLE_CUDA` to the
redzone allocator. This will be fixed in a follow up change.
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PR_kwDOArmXAs5r2G3h
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patch https://github.com/openxla/xla/pull/11225 to fix indexing maps
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patch https://github.com/openxla/xla/pull/11225 to fix indexing maps
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I_kwDOArmXAs6Ey_k-
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`floating point exception` in `tf.nn.max_pool3d` when value of `ksize` is too large.
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[
"@xl1043237213,\r\nIt's not being killed because of TF. You are literally allocating so much memory that the OS is killing the process. It seems like you're giving large negative value for multiple arguments to the function. so due to Integer overflow to buffer overflow or due to insufficient memory (RAM), code is crashing or the process getting killed and I was able to replicate the issue on Google colab. Could you please specify the usecase where you are trying with the large ksize.\r\n\r\ninput:\tA 5-D Tensor of the format specified by data_format.\r\nksize:\tAn int or list of ints that has length 1, 3 or 5. The size of the window for each dimension of the input tensor.\r\n\r\nThank you!",
"Thanks for your response. : )\r\nI found the problem with a self-designed fuzzy testing tool, and have not yet found a relevant application scenario that requires setting ksize to such a large value. However, when the value of ksize is accessible to the user, packed in the model, it can cause the program to hang or even crash.",
"I was able to reproduce the issue on tensorflow [v2.15](https://colab.research.google.com/gist/tilakrayal/37b09ac521f769a066af3508d89fe44d/untitled1857.ipynb) and v2.16. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/7b52e2e87495521a3ac7b0a5b30919f9/untitled1858.ipynb)."
] | 2024-04-05T12:49:16 | 2024-04-16T17:13:56 | null |
NONE
| null | null | null |
### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
binary
### TensorFlow version
tf 2.15
### Custom code
No
### OS platform and distribution
Linux Ubuntu 20.04
### Mobile device
_No response_
### Python version
3.10
### Bazel version
_No response_
### GCC/compiler version
_No response_
### CUDA/cuDNN version
_No response_
### GPU model and memory
_No response_
### Current behavior?
`floating point exception` in `tf.nn.max_pool3d` when value of `ksize` is too large, which will cause a crash. This crash occurs in the CPU execution environment.
### Standalone code to reproduce the issue
```shell
https://colab.research.google.com/drive/1S9D9zdhknu9ReoPahd0_kw2OEuRxLAvB?usp=sharing
```
### Relevant log output
```shell
Floating point exception (core dumped)
```
|
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PR_kwDOArmXAs5r1vn4
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Integrate LLVM at llvm/llvm-project@8487e05967aa
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Integrate LLVM at llvm/llvm-project@8487e05967aa
Updates LLVM usage to match
[8487e05967aa](https://github.com/llvm/llvm-project/commit/8487e05967aa)
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PR_kwDOArmXAs5r1uAc
| 65,118 |
Enable latest ops and subgraph reshaping in OS Bazel builds
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Enable latest ops and subgraph reshaping in OS Bazel builds
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PR_kwDOArmXAs5r1WJO
| 65,117 |
Reverts 98493bf56e3e25a40d89797b070809c05d42d6ce
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NONE
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Reverts 98493bf56e3e25a40d89797b070809c05d42d6ce
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PR_kwDOArmXAs5r0vnn
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[XLA] Add argument and return shardings to while body and cond based on result shardings if present.
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NONE
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[XLA] Add argument and return shardings to while body and cond based on result shardings if present.
This is needed in case propagation runs before this conversion, in which case the best indicator for the argument and return shardings are the shardings of the while results.
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PR_kwDOArmXAs5r0tb5
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Integrate LLVM at llvm/llvm-project@5ed60ffd790a
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Integrate LLVM at llvm/llvm-project@5ed60ffd790a
Updates LLVM usage to match
[5ed60ffd790a](https://github.com/llvm/llvm-project/commit/5ed60ffd790a)
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/11164 from Cjkkkk:bump_to_ptx81_cuda12.1 b04703e5fced0937bdb68f177ad908bcec3d153c
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I_kwDOArmXAs6Extiu
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Interpreter API (Java) - GpuDelegateV2 support
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"Hi @cfasana,\r\n\r\nThe Java Interpreter API currently doesn't have GpuDelegateV2 directly. However if you would like to achieve the faster inference speed you can use `GpuDelegate` class by setting the `isPrecisionLossAllowed` flag to `true` in the following way as a workaround. But for memory usage and max precision, feature requests will be raised. Thanks for letting us know.\r\n```\r\nGpuDelegateOptions options = new GpuDelegateOptions();\r\noptions.isPrecisionLossAllowed = true; \r\nGpuDelegate gpuDelegate = new GpuDelegate(options);\r\nInterpreterOptions interpreterOptions = new InterpreterOptions();\r\ninterpreterOptions.addDelegate(gpuDelegate);\r\nInterpreter interpreter = new Interpreter(modelBuffer, interpreterOptions);\r\n```\r\nor \r\nAlso try with tflite_flutter library which will provide access to GpuDelegateV2 through DART API.\r\n\r\nHi @pkgoogle,\r\nAs @cfasana mentioned, `GpuDelegateV2` need to be included in Java Interpreter API with the support of ```(TFLITE_GPU_INFERENCE_PRIORITY_MIN_LATENCY, TFLITE_GPU_INFERENCE_PRIORITY_MIN_MEMORY_USAGE, TFLITE_GPU_INFERENCE_PRIORITY_MAX_PRECISION)```. Raised a feature request.\r\n\r\nThank You",
"Hi @LakshmiKalaKadali,\r\nthanks for the feedback.\r\nI will proceed as you suggested while awaiting the Java Interpreter API update.",
"Hi @sirakiin, can you please take a look a this feature request? Thanks."
] | 2024-04-05T10:11:23 | 2024-04-12T20:17:40 | null |
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| null | null | null |
Hi,
I am trying to run a TFLite model on the GPU of an Android device.
According to this [documentation](https://www.tensorflow.org/lite/android/delegates/gpu), it is possible to use both the `Interpreter API` and the `Native c++ API` to achieve this.
At the moment, I am using the following dependencies:
```
implementation 'org.tensorflow:tensorflow-lite:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-select-tf-ops:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-support:0.4.4'
implementation 'org.tensorflow:tensorflow-lite-gpu:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-gpu-api:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-gpu-delegate-plugin:0.4.4'
```
I was able to successfully run my model using the `GPUDelegate` provided by the Java Interpreter API. However, this delegate does not allow to specify inference priority options (`TFLITE_GPU_INFERENCE_PRIORITY_MIN_LATENCY`, `TFLITE_GPU_INFERENCE_PRIORITY_MIN_MEMORY_USAGE`, `TFLITE_GPU_INFERENCE_PRIORITY_MAX_PRECISION`).
These options can be specified if the Native C++ API is used given the presence of GpuDelegateV2. However, at the moment I don't see this option in the Interpreter API since there is no class named `GpuDelegateV2`.
Is there a way to make use of this new delegate without the need of using the Native C++ API?
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Set while computation back pointer more consistently.
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Set while computation back pointer more consistently.
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PR #11164: [XLA:GPU] bump up minimum PTX ISA to be 8.1 for CUDA >= 12.1
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PR #11164: [XLA:GPU] bump up minimum PTX ISA to be 8.1 for CUDA >= 12.1
Imported from GitHub PR https://github.com/openxla/xla/pull/11164
NV internal workloads facing an error rn: `error : Feature 'Kernel parameter size larger than 4352 bytes' requires PTX ISA .version 8.1 or later`. Bumping up to PTX81 solved the issue however it requires minimum CUDA 12.1 to work. So for WAR, I added a check to use PTX81 if CUDA 12.1 is available.
Copybara import of the project:
--
4a15c97bd021560c553b8f93b8c421fb8487f41e by cjkkkk <[email protected]>:
bump up minimum PTX ISA to be 8.1 for CUDA >= 12.1
--
b04703e5fced0937bdb68f177ad908bcec3d153c by cjkkkk <[email protected]>:
include cuda.h
Merging this change closes #11164
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/11164 from Cjkkkk:bump_to_ptx81_cuda12.1 b04703e5fced0937bdb68f177ad908bcec3d153c
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Rename RemoveSendDone to RemoveSendAndSendDone. Ditto for RemoveRecvDone. Make them virtual and return the new custom calls.
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Rename RemoveSendDone to RemoveSendAndSendDone. Ditto for RemoveRecvDone. Make them virtual and return the new custom calls.
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Add GetDefaultLayout to PjRtTopologyDescription. This is needed to support py_compile_only_client.
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[xla:gpu] Pass custom-call results as xla:ffi results to handlers
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[xla:gpu] Pass custom-call results as xla:ffi results to handlers
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Add unbounded dynamism test for CallOp.
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Add support for recv and recv-done HLO ops in auto-sharding
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Add support for recv and recv-done HLO ops in auto-sharding
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Add a method to get default layout in PyClient.
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When generating strategies for slice ops, consider reversed mesh shapes as well when obtaining the tensor to mesh dim mapping for slice operand strategies.
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When generating strategies for slice ops, consider reversed mesh shapes as well when obtaining the tensor to mesh dim mapping for slice operand strategies.
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Add unbounded dynamism test for CollectiveBroadcastOp.
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PR_kwDOArmXAs5rxWJP
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Implement a pass to merge requantize+dequantize for StableHLO Quantizer
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Implement a pass to merge requantize+dequantize for StableHLO Quantizer
This pass will convert req+dq pattern in the quantized fusion to dq+relu(6).
Also add an option in PipelineConfig to enable this pass. This option is defaulted to false for ODML pipeline. But enabled by server.
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PR_kwDOArmXAs5rxSD8
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[xla:ffi] Add auto-binding for FFI results
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[xla:ffi] Add auto-binding for FFI results
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PR_kwDOArmXAs5rxRbK
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[xla:ffi] Add support for annotating FFI results with type tags to distingush them from regular args
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[xla:ffi] Add support for annotating FFI results with type tags to distingush them from regular args
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Crash on HLOs with nested tuples in conditionals.
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Crash on HLOs with nested tuples in conditionals.
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Update OpenCL wrapper when using ICD loader for Google Linux.
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[] | 2024-04-04T22:35:54 | 2024-04-04T23:39:26 | 2024-04-04T23:39:25 |
NONE
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Update OpenCL wrapper when using ICD loader for Google Linux.
Also add TFLITE_LOG to show which loading path is used.
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Add a fallback when GetDefaultLayout is unimplemented for that backend.
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NONE
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Add a fallback when GetDefaultLayout is unimplemented for that backend.
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