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tensorflow-issues

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[ "Hi @kralka ,\r\n\r\nI have replicated the issue with `TF2.15v` and `tf-nightly` as well. On Colab the code executes indefinitely due to naming collision of generator and finally runtime will crash without any logs. Attaching [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/07facdb64fa42d474b68cbe875040fd7/67566.ipynb) for reference.", "@SuryanarayanaY thank you for your response. One can get a crash (as opposed to indefinite execution without errors) in an official docker (`docker pull tensorflow/tensorflow:latest-gpu`). I will provide concrete steps if needed.", "Hi @SuryanarayanaY is there some plan to resolve this issue? Do you know what causes it? In case resolving would require too large changes do you think it is worth putting a note in the documentation since it is rather hard to figure out what causes this behavior?\r\n\r\nPersonally I would be interested in the cause of this since some magic needs to be happening here :-)", "Sorry my fault. This is not a TensorFlow issue.\r\n\r\n```python\r\nmy_list = [1, 2, 3]\r\n\r\ndef gen():\r\n yield from my_list\r\n\r\nmy_list = [5, 6, 7]\r\n\r\nassert list(gen()) == [5, 6, 7]\r\n```", "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/67566\">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/67566\">No</a>\n" ]

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[ "@fzd370 In TensorFlow v2.10, the default behavior is to choose the GPU with the lowest ID. This typically leads to selecting the integrated Intel GPU over a dedicated Nvidia GPU.Please ensure you're running your Python scripts or Jupyter notebooks within the activated virtual environment where you installed TensorFlow with GPU support. Kindly double-check your CUDA and cuDNN installations. \r\n\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/67558\">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/67558\">No</a>\n" ]

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[ "Hi @majiddadashi Any update on this PR? Please. Thank you!" ]

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[ "Hi @apach301 is this issue still open?\r\nIf so, could you tell me how to replicate the bug so that I may have a go at it?", "> Hi @apach301 is this issue still open?\n> \n> If so, could you tell me how to replicate the bug so that I may have a go at it?\n\nThis bug was detected by static analysis, therefore I have no input to reproduce it during execution. But I propose a fix in PR #67557", "Hi @apach301 the PR looks great, if you would like any help with CI, do let me know.\r\n\r\nThanks and regards", "will wait for review.", "> will wait for review.\r\n\r\nHi @pkgoogle How to enable CI tests run in PR #67557? Is it wait any approval to run?", "Hi @apach301, we'll have to wait for review, we run CI/CD internally and review the PR." ]

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[ "@AceAbhi147 Could you please confirm that you have followed the steps properly and also referred the tested build configurations? Please let us know!\r\n\r\n\r\n\r\n\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/67554\">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/67554\">No</a>\n" ]

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[ "Hi @jpienaar Any update on this PR? Please. Thank you!" ]

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[ "@tanpengshi The FlexDelegate functionality is integrated within the TensorFlow Lite interpreter itself when built with Select Ops enabled. Could you please upgrade to the latest TF version and let us know as the older TF versions are not actively supported. Thank you!", "I have tried invoking the interpreter and I get the error\r\n\r\n```\r\n guard let interpreter = tflite else {\r\n print(\"TFLite Error: Interpreter is nil.\")\r\n return\r\n }\r\n do {\r\n let inputData = Data(buffer: UnsafeBufferPointer(start: dataBuffer, count: dataBuffer.count))\r\n try interpreter.copy(inputData, toInputAt: 0)\r\n try interpreter.invoke()\r\n\r\n let output = getTensorOutput(interpreter: interpreter)\r\n let detectedActionIndex = output.argmax()\r\n print(\"Detected Action Index is: \\(detectedActionIndex)\")\r\n } catch {\r\n print(\"TFLite Error: \\(error.localizedDescription)\")\r\n }\r\n```\r\n\r\nTensorFlow Lite Error: Select TensorFlow op(s), included in the given model, is(are) not supported by this interpreter. Make sure you apply/link the Flex delegate before inference. For the Android, it can be resolved by adding \"org.tensorflow:tensorflow-lite-select-tf-ops\" dependency. See instructions: https://www.tensorflow.org/lite/guide/ops_select\r\nTensorFlow Lite Error: Node number 76 (FlexTensorListReserve) failed to prepare.\r\nTFLite Error: Must call allocateTensors().\r\n\r\nI have already \"import TensorFlowLiteSelectTfOps\" in my Swift file. \r\n\r\n\r\n\r\nI have accidentally deleted the CoreMLDelegate and also the MetalDelegate from the library. Would it cause this error? I have deleted these libraries and I don't know how to recover them. When I do:\r\n\r\n```\r\nrm -rf Pods Podfile.lock\r\npod install\r\n```\r\n\r\nThe files are still missing. I really appreciate your help! I have come very close to the solution for my App!\r\n", "@tanpengshi Directly recovering deleted libraries from within your project isn't possible. Could you try to use the latest TFlite version as newer versions might include these delegates within the framework itself, eliminating the need for separate libraries. After reinstalling/updating, clean and rebuild your project to ensure the changes take effect.\r\n\r\nThank you!", "Are you suggesting that I recreate a new project?\r\n\r\nNow i proceed to try a more conventional method using the Podfile:\r\n\r\n```\r\n# Uncomment the next line to define a global platform for your project\r\nplatform :ios, '17.0'\r\n\r\ntarget 'FacialRecognition' do\r\n # Comment the next line if you don't want to use dynamic frameworks\r\n use_frameworks!\r\n #pod 'TensorFlowLiteSwift', :path => '../../local-podspecs/TensorFlowLiteSwift.podspec'\r\n # pod 'TensorFlowLiteSelectTfOps', :path => '../../local-podspecs/TensorFlowLiteSelectTfOps.podspec'\r\n # pod 'TensorFlowLiteSwift' # or 'TensorFlowLiteObjC'\r\n # pod 'TensorFlowLiteSelectTfOps', '~> 0.0.1-nightly'\r\n\r\n\r\n pod 'TensorFlowLiteSwift'\r\n pod 'TensorFlowLiteSelectTfOps', '~> 0.0.1-nightly'\r\n\r\n # Pods for FacialRecognition\r\n\r\n target 'FacialRecognitionTests' do\r\n inherit! :search_paths\r\n # Pods for testing\r\n end\r\n\r\n target 'FacialRecognitionUITests' do\r\n # Pods for testing\r\n end\r\n\r\n # Add these lines to ensure consistent EXCLUDED_ARCHS settings\r\n post_install do |installer|\r\n installer.pods_project.targets.each do |target|\r\n target.build_configurations.each do |config|\r\n config.build_settings['EXCLUDED_ARCHS[sdk=iphonesimulator*]'] = 'arm64'\r\n end\r\n end\r\n end\r\n\r\nend\r\n```\r\n\r\nBut when I build my project, I get:\r\n\r\n\r\n\r\nWhen I check the 'Pods' directory, I don't see a 'resources-to-copy-FacialRecognition' file", "I am now able to solved the issue above and the TensorFlow Lite model with SelectOps is able to successfully run by following the suggestion here:\r\n\r\n[https://stackoverflow.com/questions/76792138/sandbox-bash72986-deny1-file-write-data-users-xxx-ios-pods-resources-to-co](https://stackoverflow.com/questions/76792138/sandbox-bash72986-deny1-file-write-data-users-xxx-ios-pods-resources-to-co)\r\n\r\nHowever my app size is over 200MB because of the library! Hence, I need to do a Selective Build which effectively return me to the first solution. In my Podfile, I did for the first solution:\r\n\r\n```\r\nplatform :ios, '17.0'\r\n\r\ntarget 'FacialRecognition' do\r\n # Comment the next line if you don't want to use dynamic frameworks\r\n use_frameworks!\r\n pod 'TensorFlowLiteSwift', :path => '../../local-podspecs/TensorFlowLiteSwift.podspec'\r\n\r\n # Pods for FacialRecognition\r\n\r\n target 'FacialRecognitionTests' do\r\n inherit! :search_paths\r\n # Pods for testing\r\n end\r\n\r\n target 'FacialRecognitionUITests' do\r\n # Pods for testing\r\n end\r\n\r\n # Add these lines to ensure consistent EXCLUDED_ARCHS settings\r\n post_install do |installer|\r\n installer.pods_project.targets.each do |target|\r\n target.build_configurations.each do |config|\r\n config.build_settings['EXCLUDED_ARCHS[sdk=iphonesimulator*]'] = 'arm64'\r\n end\r\n end\r\n end\r\n\r\nend\r\n```\r\n\r\nIn my TensorFlowLiteSwift.podspec file, I have:\r\n\r\n```\r\nPod::Spec.new do |s|\r\n s.name = 'TensorFlowLiteSwift'\r\n s.version = '2.7.0'\r\n s.authors = 'Google Inc.'\r\n s.license = { :type => 'Apache' }\r\n s.homepage = 'https://github.com/tensorflow/tensorflow'\r\n s.source = { :git => 'https://github.com/tensorflow/tensorflow.git', :tag => \"v#{s.version}\" }\r\n s.summary = 'TensorFlow Lite for Swift'\r\n s.description = <<-DESC\r\n\r\n TensorFlow Lite is TensorFlow's lightweight solution for Swift developers. It\r\n enables low-latency inference of on-device machine learning models with a\r\n small binary size and fast performance supporting hardware acceleration.\r\n DESC\r\n\r\n s.ios.deployment_target = '17.0'\r\n\r\n s.module_name = 'TensorFlowLite'\r\n s.static_framework = true\r\n\r\n tfl_dir = 'tensorflow/lite/'\r\n swift_dir = tfl_dir + 'swift/'\r\n\r\n s.default_subspec = 'Core'\r\n\r\n s.subspec 'Core' do |core|\r\n # Adjust the path to point to your custom frameworks\r\n core.vendored_frameworks = [\r\n 'frameworks/TensorFlowLiteC.framework',\r\n 'frameworks/TensorFlowLiteSelectTfOps.framework'\r\n ]\r\n \r\n core.source_files = swift_dir + 'Sources/*.swift'\r\n core.exclude_files = swift_dir + 'Sources/{CoreML,Metal}Delegate.swift'\r\n\r\n core.test_spec 'Tests' do |ts|\r\n ts.source_files = swift_dir + 'Tests/*.swift'\r\n ts.exclude_files = swift_dir + 'Tests/MetalDelegateTests.swift'\r\n ts.resources = [\r\n tfl_dir + 'testdata/add.bin',\r\n tfl_dir + 'testdata/add_quantized.bin',\r\n ]\r\n end\r\n end\r\n\r\n s.subspec 'CoreML' do |coreml|\r\n coreml.source_files = swift_dir + 'Sources/CoreMLDelegate.swift'\r\n coreml.dependency 'TensorFlowLiteSwift/Core', \"#{s.version}\"\r\n end\r\n\r\n s.subspec 'Metal' do |metal|\r\n metal.source_files = swift_dir + 'Sources/MetalDelegate.swift'\r\n metal.dependency 'TensorFlowLiteSwift/Core', \"#{s.version}\"\r\n\r\n metal.test_spec 'Tests' do |ts|\r\n ts.source_files = swift_dir + 'Tests/{Interpreter,MetalDelegate}Tests.swift'\r\n ts.resources = [\r\n tfl_dir + 'testdata/add.bin',\r\n tfl_dir + 'testdata/add_quantized.bin',\r\n tfl_dir + 'testdata/multi_add.bin',\r\n ]\r\n end\r\n end\r\nend\r\n```\r\n\r\nBut using this method, with MetalDelegate and CoreMLDelegate libraries deleted, I have FlexDelegate not found error.\r\n", "@tanpengshi Thank you for the update. Glad the issue has been resolved. \r\nCould you please let us know if we can close the issue?\r\nThank you!", "Sure, we can close this issue, and I will open a next one regarding the new issue", "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/67538\">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/67538\">No</a>\n", "@tanpengshi Thank you!" ]

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