Datasets:

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Isuru0x01

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tensorflow-issues

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[ "Hi @chengdazhi ,\r\n\r\nI tested the code with Tf2.12v and I can see the gradients returned by them are almost equal (with precision related differences of order `e-06` range). Also curious why the sample code snippet uses two gradient tapes as there are no second order gradients here. \r\n\r\nAnyways I have tested the code with both ways and results are same except some precision related differences of order \r\n**e-06** range. Please refer attached [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/2d8a7aa556651ef701814dce1e69a2de/61675_tf-linalg-inv_pinv.ipynb).\r\n\r\nCould you please test with latest versions and let us know the results.\r\n\r\nThanks!", "Hi @SuryanarayanaY Thanks for your speedy response. I handcrafted another matrix in [gist](https://colab.research.google.com/gist/chengdazhi/be84e8163d7c5adf810ddd3045d42faa/61675_tf-linalg-inv_pinv.ipynb), and it seems the gradient difference is still pretty large (order e-2).\r\n\r\n\r\n\r\n\r\n", "@chengdazhi ,\r\n\r\nTested the updated code and found differences upto e-02 order. Attached [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/5a924806383ff8f32b0fbf40139bb0fc/61675_tf-linalg-inv_pinv-r1.ipynb) for reference. Will escalate to Dev team for their review. Thanks!\r\n", "I think that's still within expected numerical precision. The entries where you see the large \"error\" are near (or exactly) zero in your inverse, which makes them particularly sensitive to small numerical perturbations. The pseudo inverse needs to do a lot more computation, since it does an SVD, which means small floating-point errors accumulate more.", "@cantonios I don't think so. The se3_mat I created is actually pretty well-conditioned. Btw same code seems legit in pytorch.\r\nSee the [gist](https://colab.research.google.com/gist/chengdazhi/be84e8163d7c5adf810ddd3045d42faa/61675_tf-linalg-inv_pinv.ipynb#scrollTo=Y-MT7i-T1DxX). I feel there's a bug somewhere.\r\n\r\n\r\n\r\n\r\n" ]

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[ "@sachinprasadhs,\r\nI was able to reproduce the issue on the tf-nightly(2.15.0-dev20230817) whereas on tensorflow v2.12 and v2.13, the code was executed without any issue/error. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/bd60586f3fd8c2c75c6840fca6a41fe1/untitled1339.ipynb). " ]

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[ "@pro1944191 ,\r\n\r\nFor uninstalling Tf2.13v, please try `pip uninstall tensorflow==2.13` for uninstalling Tf2.13v and the install Tf2.10 again with `pip install tensorflow==2.10` . \r\n\r\nFor details on accessing windows files from wsl2 please refer to this [resource](https://learn.microsoft.com/en-us/windows/wsl/filesystems).", "Thank you for you answer, I tried with `pip install tensorflow==2.10` but I got this error message from pip **ERROR: Could not find a version that satisfies the requirement tensorflow==2.10* (from versions: 2.12.0rc0, 2.12.0rc1, 2.12.0, 2.12.1, 2.13.0rc0, 2.13.0rc1, 2.13.0rc2, 2.13.0, 2.14.0rc0)\r\nERROR: No matching distribution found for tensorflow==2.10***", "Hey @pro1944191 i think you little bit messed up things. May i know `tf` version on both `WSL2 venv` & `conda env`? What os you wanna work on `linux(WSL2)` or `windows` ?", "You can install `tf==2.10` using `conda` too. Check here: [anaconda tf 2.10 binaries ](https://anaconda.org/anaconda/tensorflow/files?version=2.10.0)\r\nor you can retry with pip as ([pypi project](https://pypi.org/project/tensorflow/2.10.0/)):\r\n```\r\npip install tensorflow==2.10.0\r\n```", "Hi @pro1944191 ,\r\n\r\nI believe there is mix of Conda and Pip installations here causing the issue. We recommend to use only pip for installing tf binaries and refer the official [source](https://www.tensorflow.org/install/pip#:~:text=Note%3A%20Do%20not%20install%20TensorFlow%20with%20conda.%20It%20may%20not%20have%20the%20latest%20stable%20version.%20pip%20is%20recommended%20since%20TensorFlow%20is%20only%20officially%20released%20to%20PyPI.) for same. Could you please try with fresh environments.", "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." ]

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[]

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[ "Possibly duplicate of https://github.com/tensorflow/tensorflow/issues/37580 (closed due to inactivity)", "@SuryanarayanaY I was able to replicate the issue on colab, please find the [gist](https://colab.research.google.com/gist/sushreebarsa/9b5c90b9ec2eeaa20c04883f15376123/floatlist_np_vs_tf.ipynb#scrollTo=17nKROKLTO3A) here. Thank you!", "Thanks @kralka, I think what happens is that the construction of the proto message iterates over the entire array.\r\n\r\nThis iteration is a lot slower in TF than NumPy because the indexing method in TF is [pretty complicated](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.py#L979). We would like to improve the performance but it's not a priority right now.\r\n\r\nIt seems you already have a workaround for the original example. However if slow indexing is causing you trouble, please feel free to file a separate bug to discuss it.", "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/61671\">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/61671\">No</a>\n" ]

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[ "The Py+CPP Test Suite failure is due to a flaky test and is not the result of this PR" ]

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[ "@NaToh5 You're encountering compatibility issues with TensorFlow 1.13.1, your RTX 3060 GPU, and the CUDA 10.0 version. The primary recommendation is to upgrade TensorFlow to a more recent version that is better suited for your RTX 3060 GPU and CUDA 10.0. TensorFlow 1.13.1 predates this hardware and might not work optimally. Keep in mind that upgrading TensorFlow might require some code adjustments due to changes in the API and the way TensorFlow's updated version handles certain operations.", "@AyushChauhan-ui Thank you for your reply. Can I use tensorflow-gpu 1.15.0 with my RTX 3060 and cuda version 10 or 11? I cannot use more advance tensorflow version on that Octopus model because that model is quite old and only working on tensorflow-gpu old version. \r\n\r\nOr how can I use tensorflow-gpu 1.13.1 ? Should I change my GPU and cuda?", "Hi @NaToh5 ,\r\n\r\nFor tensorflow-gpu version 1.13.1 and above, the CUDA version has to be 10.\r\nPlease refer the built configurations [here](https://www.tensorflow.org/install/source#gpu).\r\n\r\nThank you!!", "@Varsha-anjanappa so the issue is coming from my RTX 3060 GPU card or cuda ? I already install cuda 10.0 and still not working. ", "@NaToh5 CUDA 10 may not be compatible with RTX3060. Tensorflow 1.15.0 might work. You can try a newer version of CUDA.", "@AyushChauhan-ui thank you for your reply. The model cannot change to tensorflow upgraded version. Look like only working on tensorflow -gpu 1.13.1 . Do you think it might work when I upgrade to cuda 11 version with tensorflow 1.13.1 ?", "@NaToh5 Well Tensorflow 1.13.1 supports only upto CUDA 10. This combination will work but your RTX3060 will not be compatible with them.", "@AyushChauhan-ui It's working well on my old laptop with cuda 10 (tensorflow 1.13.1). Do you think 1.15.0 will work on cuda 11 ? ", "@NaToh5 Tensorflow 1.13.1 works well with CUDA 10 but they are not compatible with RTX3060.", "@NaToh5 Sorry I mean tensorflow-gpu 1.15.0 will compatible with cuda 11.5? ", "@NaToh5 Check the compatibility combinations here (https://www.tensorflow.org/install/source#gpu)", "@AyushChauhan-ui Thank you!!", "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/61669\">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/61669\">No</a>\n" ]

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[ "@cfRod @nSircombe @penpornk @thaink ", "@elfringham From your comparison, what is the main difference between those two libs?", "@thaink \r\nWhen running ldd on pywrap_saved_model.so you get\r\n_pywrap_tensorflow_internal.so => /workspace/venv_bad/lib/python3.11/site-packages/tensorflow/python/saved_model/../_pywrap_tensorflow_internal.so (0x0000ffffa1c0a000)\r\n\r\nWhen running ldd on pywrap_quantize_model.so you get\r\n_pywrap_tensorflow_internal.so => not found\r\nSo it looks like RPATH is not set correctly.", "@thaink \r\nYes, RPATH does not contain the location of _pywrap_tensorflow_internal.so\r\n\r\n$ ls -l venv_bad/lib/python3.11/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so\r\n-rwxrwxr-x 1 andrew andrew 2513424 Aug 18 14:23 venv_bad/lib/python3.11/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so\r\n$ patchelf --print-rpath venv_bad/lib/python3.11/site-packages/tensorflow/compiler/mlir/quantization/tensorflow/python/pywrap_quantize_model.so\r\n$ORIGIN/../../../../../../_solib_local/_U_S_Stensorflow_Clibtensorflow_Uframework_Uimport_Ulib___Utensorflow:$ORIGIN/pywrap_quantize_model.so.runfiles/org_tensorflow/_solib_local/_U_S_Stensorflow_Clibtensorflow_Uframework_Uimport_Ulib___Utensorflow:$ORIGIN/../../../../../../_solib_local/_U_S_Stensorflow_Spython_C_Upywrap_Utensorflow_Uinternal_Ulinux___Utensorflow_Spython:$ORIGIN/pywrap_quantize_model.so.runfiles/org_tensorflow/_solib_local/_U_S_Stensorflow_Spython_C_Upywrap_Utensorflow_Uinternal_Ulinux___Utensorflow_Spython:$ORIGIN/:$ORIGIN/..:$ORIGIN/../..:$ORIGIN/../../..:$ORIGIN/../../../..:$ORIGIN/../../../../..", "Thanks for reporting and fixing @elfringham ", "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/61668\">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/61668\">No</a>\n" ]

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[ "Hi @mrousavy \r\n\r\nAs per the [documentation](https://www.tensorflow.org/lite/android/development#tflite_c_api_2), \r\n\r\nCurrently, there is no straightforward way to extract all header files needed, we need include all header files manually.\r\n\r\n@pkgoogle Could you please look at this request?\r\n\r\nThanks.\r\n", "Hi @mrousavy, I can't find any documentation that we have a prefab available, should we take this as a feature request?", "Hey - yea sorry this was a question at first, but if that's not a feature then it's a feature request I guess :)\r\n\r\nHappy to help here - but prefabs are really making things a lot easier for us C++ developers. Thanks!", "Hi @arfaian, can you please take a look? Thanks." ]

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[ "You seem to be running TensorFlow that was installed for Python 3.9 but using Python 3.11 interpreter. Of course it fails.", "What is the output of `python -m pip list; python -c \"import tensorflow as tf; print(tf)\"`?\r\n\r\n(replace `python` with `python3` / `python3.9` / `python3.11`, accordingly)", "@danche354 Could you please make sure that you are using compatible version as mentioned [here](https://www.tensorflow.org/install/source) under tested build configuration and followed the exact steps? \r\nPlease cross check the python version you are using!\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/61666\">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/61666\">No</a>\n" ]

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[ "Hi @andrewkim-pkt ,\r\n\r\nTry using Clang instead of GCC, as from tf v2.13 it supports compiler Clang. Please refer the documentation [here](https://www.tensorflow.org/install/source#cpu) for reference. Let us know if the issue still exists. \r\n\r\nThank you!!", "GCC 11.4 build with tr v2.13 works fine but GCC 12.2 got this issue.\r\nNever tried it with Clang, can you please share the steps for this to save time.\r\n\r\nFrom: Varsha-anjanappa ***@***.***>\r\nSent: Monday, August 21, 2023 11:54 PM\r\nTo: tensorflow/tensorflow ***@***.***>\r\nCc: Kim, Andrew ***@***.***>; Mention ***@***.***>\r\nSubject: Re: [tensorflow/tensorflow] `GLIBCXX_3.4.30' not found (Issue #61665)\r\n\r\n\r\nHi @andrewkim-pkt<https://github.com/andrewkim-pkt> ,\r\n\r\nTry using Clang instead of GCC, as from tf v2.13 it supports compiler Clang. Please refer the documentation here<https://www.tensorflow.org/install/source#cpu> for reference. Let us know if the issue still exists.\r\n\r\nThank you!!\r\n\r\n—\r\nReply to this email directly, view it on GitHub<https://github.com/tensorflow/tensorflow/issues/61665#issuecomment-1687580470>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AG5F7EB4IKY6IVIB35Q2SULXWRJRHANCNFSM6AAAAAA3ZLZ6XU>.\r\nYou are receiving this because you were mentioned.Message ID: ***@***.******@***.***>>\r\n", "Hi @andrewkim-pkt ,\r\n\r\nPlease follow the build from source steps [here](https://www.tensorflow.org/install/source).\r\nTo install clang please refer [here](https://www.tensorflow.org/install/source#install_clang_recommended_linux_only).\r\nConfigure the build and select Y to use Clang to build TensorFlow. Refer [here](https://www.tensorflow.org/install/source#expandable-1)\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/61665\">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/61665\">No</a>\n" ]

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[ "Hi @Mayi-Keiji \r\n\r\nThe input shape of the Keras model is observed as `(None,None,None,3)` and when converted to TFLite model it becomes shape `(1,1,1,3)`\r\n\r\nIf you want to run a model with dynamic input shape, resize the input shape before running inference. Otherwise, the None shape in Tensorflow models will be replaced by a placeholder of 1 in TFLite models.\r\n\r\nResizing the tensor with specific shape should solve the problem.\r\n\r\n```\r\ninterpreter = tf.lite.Interpreter(model_path=\"model.tflite\")\r\ninterpreter.resize_tensor_input(interpreter.get_input_details()[0]['index'], [1,224,224,3])\r\ninterpreter.allocate_tensors()\r\n\r\n# Get input and output tensors.\r\ninput_details = interpreter.get_input_details()\r\noutput_details = interpreter.get_output_details()\r\nprint(input_details)\r\n\r\n# Test the model on random input data.\r\ninput_shape = [1,224,224,3]\r\ninput_data = np.array(np.random.random_sample(input_shape), dtype=np.float32)\r\ninterpreter.set_tensor(input_details[0]['index'], input_data)\r\n\r\ninterpreter.invoke()\r\n\r\n# The function `get_tensor()` returns a copy of the tensor data.\r\n# Use `tensor()` in order to get a pointer to the tensor.\r\noutput_data = interpreter.get_tensor(output_details[0]['index'])\r\nprint(output_data)\r\n```\r\n\r\nPlease find this resolved [gist](https://colab.research.google.com/gist/pjpratik/d4c86f7ccf73cb2d82ee592dd83e7ed9/61664.ipynb) for the same and let us know if it helps.\r\n\r\nThanks.", "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 had the same issue and it was related to the input shape. @pjpratik thanks for helping me realise that!", "@NIKovachev Glad it helped.\r\n\r\n@Mayi-Keiji Feel free to close the issue if it is resolved.\r\n\r\nThanks.", "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/61664\">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/61664\">No</a>\n" ]

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[ "Hi @anselmo0v \r\n\r\nAs per the [documentation](https://www.tensorflow.org/lite/api_docs/python/tf/lite/TargetSpec#attributes), it should only be used if we are using TF ops that may not be linked in by default with the TF ops that are provided when using the SELECT_TF_OPS path.\r\n\r\nI guess adding the regular select ops flag does the similar job as `RandomUniform` and `Mul `are already a part of [Select TF Ops](https://www.tensorflow.org/lite/guide/op_select_allowlist#tensorflow_core_operators). Please check this [gist](https://colab.research.google.com/gist/pjpratik/7860512ac86d586c96365cad4bf9d711/61662.ipynb).\r\n\r\nFor reducing the binary size of the TFLite model consider https://www.tensorflow.org/lite/guide/reduce_binary_size\r\n\r\nThanks.", "Hi @pjpratik, thank you very much for your response.\r\n\r\nSo, I understand what I am doing is not the intended use for the experimental_select_user_tf_ops flag. I had checked the guide to reduce binary size before, the thing is my laptop is freezing in the middle of the build with bazel when I set SELECT_TF_OPS, and that's why I wanted to reduce the number of ops included. \r\n\r\nAny chance there is a method to manually specify just some ops from the tf_ops set to be included in the build?", "Hi @anselmo0v \r\n\r\nThanks for the information.\r\n\r\nAs of now, we can only reduce the binary size by model, not using the list of ops. Selective building will include the necessary operators for your models.\r\n\r\n> I had checked the guide to reduce binary size before, the thing is my laptop is freezing in the middle of the build with bazel when I set SELECT_TF_OPS\r\n\r\nRegarding freezing issues during Bazel builds with the SELECT_TF_OPS flag, it's advisable to consider using a more powerful machine with robust CPU and memory configurations for smooth compilation of model, incase they are complex. \r\n\r\nIs it possible to share the error stack trace and TFLite model to reproduce the issue?\r\n\r\nThanks.\r\n\r\n", "Hi @pjpratik,\r\n\r\nI'll try to find a better machine to run the build and contact again with error trace if any. \r\n\r\nThank you very much for your help.", "Hi @anselmo0v \r\n\r\nDid you get a chance to run the build?\r\n\r\nThanks.", "Hi @pjpratik.\r\n\r\nYes, I have been following the reduce binary size [guide](https://www.tensorflow.org/lite/guide/reduce_binary_size) in various machines both Mac and Linux with no sucess at building tensorflowlite_flex. \r\n\r\nI decided to use an AWS EC2 instance with Docker to avoid possible dependency conflicts, but still the build fails. The instance has this specifications:\r\n\r\nRAM: 32GB\r\nvCPU: 16\r\nArchitecture: x86_64\r\nOS: Ubuntu 22.0.4 Server\r\n\r\nI use the same simple model of my first comment, previously converted and saved to a .tflite, setting _tf.lite.OpsSet.TFLITE_BUILTINS_ and _tf.lite.OpsSet.SELECT_TF_OPS_ .\r\n\r\nThese are the BUILD file inside the created _tmp_ folder and the Dockerfile I am using:\r\n[Dockerfile.txt](https://github.com/tensorflow/tensorflow/files/12551233/Dockerfile.txt)\r\n[BUILD.txt](https://github.com/tensorflow/tensorflow/files/12551234/BUILD.txt)\r\n\r\nThis is the error I get:\r\n[error_logs.txt](https://github.com/tensorflow/tensorflow/files/12551260/error_logs.txt)\r\n\r\nIt seems to be a consistent error in all the Intel - Linux machines I've tried. At lines _52 to 60_ of my Dockerfile I tried to solve this issue by including the source files from oneAPI into the source files of Tensorflow, but the same error keeps showing.\r\n\r\nI appreciate your help.", "Hi @pjpratik .\r\n\r\nSo I followed the [guide](https://www.tensorflow.org/lite/android/lite_build) to build .aar files for Java from the AWS EC2 instance I mentioned before and it was successful. \r\n\r\nNow I've tried to follow similar steps to build for C++. I've copied and modified the build_aar.sh file:\r\n[build_tf_flex.sh](https://github.com/tensorflow/tensorflow/files/12591917/build_tf_flex.txt)\r\n\r\nAnd divided my previous BUILD file into to different files:\r\n[BUILD_tfliteops](https://github.com/tensorflow/tensorflow/files/12591931/BUILD_tfliteops.txt)\r\n[BUILD_tfops](https://github.com/tensorflow/tensorflow/files/12591925/BUILD_tfops.txt)\r\n\r\nI also deleted lines _52 to 60_ (that added oneapi source files) from my Dockerfile:\r\n[Dockerfile](https://github.com/tensorflow/tensorflow/files/12591937/Dockerfile.txt)\r\n\r\nThe _tensorflowlite.so_ file is successfully created, but I get a lot of undefined reference errors when building the _tensorflowlite_flex.so_ file:\r\n[stderr-2](https://github.com/tensorflow/tensorflow/files/12591997/stderr-2.txt)\r\n\r\nThis is the command I'm using from the Docker container to build:\r\n`bash custom_files/build_tf_flex.sh --input_models=custom_files/cpp_tf_test.tflite --target_archs=arm64-v8a` Not sure if this is the correct target when building .so files for android, since other guides say you should use _android_arm64_.\r\n\r\nI can work for now with the .aar files but the reason I need to build for C++ is because I'm looking for cross platform integration.\r\n\r\nI really appreciate any help you can provide.\r\n\r\n\r\n\r\n\r\n", "Hi @anselmo0v \r\n\r\nSorry for the delayed response. Thanks for the information.\r\n\r\nJust wanted to know if you tried with just `--config=andorid_arm64` without monolithic build?\r\n\r\n```\r\nbazel build -c opt --cxxopt=--std=c++17 --config=android_arm64 --host_crosstool_top=@bazel_tools//tools/cpp:toolchain //tmp:tensorflowlite_flex \r\n```\r\n\r\nThanks.\r\n\r\n", "Hi @pjpratik.\r\n\r\nI retried as suggested, no `--config=monolithic` option and using `--confing=android_arm64` as target.\r\n\r\nThis is my new .sh file:\r\n[build_tf_flex.sh](https://github.com/tensorflow/tensorflow/files/12694149/build_tf_flex_2.txt)\r\n\r\nIt is back to the error related to missing dnnl files:\r\n[error_logs](https://github.com/tensorflow/tensorflow/files/12694147/error_logs_2.txt)\r\n\r\n", "Hi @anselmo0v \r\n\r\nThanks for the information.\r\n\r\n@pkgoogle Could you please check this issue?\r\n", "Hi @anselmo0v, Can you review this and see if it helps you.\r\nhttps://www.tensorflow.org/lite/guide/ops_select#cc\r\nhttps://www.tensorflow.org/lite/android/development#tools_for_building_with_c_and_c\r\n\r\nif that doesn't work can you please give me your exact steps (as if you are writing a shell script or Dockerfile) to reproduce the issue you are seeing. There's probably a way to get it from all the above but putting it all into one message will make things easier to debug.", "Hi @pkgoogle, thanks for taking a look at this issue. These are the steps I'm following:\r\n\r\n**1.** I create my .tflite file from this Google Colab Notebook [here](https://github.com/anselmo0v/test-tf-lite/blob/main/tflite_dummy_model.ipynb).\r\n\r\n**2.** I connect my local terminal by ssh to the AWS EC2 instance I use (RAM: 32GB, vCPU: 16, Architecture: x86_64, OS: Ubuntu 22.0.4 Server).\r\n\r\n**3.** I clone [my files](https://github.com/anselmo0v/test-tf-lite/tree/main/tf-builder-docker) from terminal.\r\n\r\n**4.** Then I build the docker image from my [Dockerfile](https://github.com/anselmo0v/test-tf-lite/blob/main/tf-builder-docker/Dockerfile):\r\n```\r\n cd tf-builder-docker\r\n sudo docker build . -t tf-builder -f Dockerfile\r\n```\r\n\r\n**5.** Next I run the container and go inside it:\r\n`sudo docker run -it -v $PWD:/host_dir tf-builder bash`\r\n\r\n**6.** Inside the running container, I go to the tensorflow source folder:\r\n`cd home/tensorflow-2.13.0`\r\n\r\n**7.** From there, I run my [build_tf_flex.sh](https://github.com/anselmo0v/test-tf-lite/blob/main/tf-builder-docker/build_tf_flex.sh) file:\r\n`bash custom_files/build_tf_flex.sh --input_models=custom_files/cpp_tf_test.tflite --target_archs=android_arm64`\r\n\r\nThe custom_files folder is created at my Dockerfile and contains the BUILD files, the build_tf_flex.sh file and the .tflite model. \r\n\r\nThe build_tf_flex.sh file is a customized file I made by taking the build_aar.sh file from tensorflow source code and modifying it to:\r\n\r\n - Build the tensorflowlite.so with the command: \r\n bazel ${CACHE_DIR_FLAG} build -c opt --cxxopt='--std=c++17' --config=${TARGET_ARCHS} //tmp:tensorflowlite --verbose_failures\r\n \r\n - Build the tensorflowlite_flex.so with the command:\r\n bazel ${CACHE_DIR_FLAG} build -c opt --cxxopt='--std=c++17' --config=${TARGET_ARCHS} --host_crosstool_top=@bazel_tools//tools/cpp:toolchain //tmp:tensorflowlite_flex --verbose_failures\r\n\r\nThe tensorflowlite.so file is successfully created, but at the tensorflowlite_flex.so building step I obtain the mentioned error:\r\n`fatal error: dnnl.hpp: No such file or directory`\r\n\r\nThis is the log file: \r\n[error_logs](https://github.com/tensorflow/tensorflow/files/12743392/error_logs_2.txt)\r\n", "Hi @anselmo0v,\r\n\r\nI was able to replicate your issue with the following steps:\r\n\r\n```\r\ngit clone https://github.com/anselmo0v/test-tf-lite.git\r\ncd test-tf-lite/tf-builder-docker\r\nsudo docker build . -t tf-builder -f Dockerfile\r\nsudo docker run -it -v $PWD:/host_dir tf-builder bash\r\ncd home/tensorflow-2.13.0\r\nbash custom_files/build_tf_flex.sh --input_models=custom_files/cpp_tf_test.tflite --target_archs=android_arm64\r\n```\r\n\r\nIt seems like that header (dnnl.hpp) is only included with some build_with_mkl flags, I tried a couple of different things but they all failed as well.\r\n\r\nI added a --define=build_with_mkl=true flag but that wasn't it, but it seems it got further\r\n```\r\n+ bazel-bin/tensorflow/lite/tools/list_flex_ops_no_kernel_main --graphs=custom_files/cpp_tf_test.tflite\r\n++ cat /home/tensorflow-2.13.0/tmp//ops_list.txt\r\n+ [[ [\"Mul\",\"RandomUniform\"] != \\[\\] ]]\r\n+ generate_flex_so\r\n+ pushd /home/tensorflow-2.13.0/tmp/\r\n/home/tensorflow-2.13.0/tmp /home/tensorflow-2.13.0\r\n+ cp /home/tensorflow-2.13.0/custom_files/BUILD_tfops /home/tensorflow-2.13.0/tmp//BUILD\r\n+ popd\r\n/home/tensorflow-2.13.0\r\n+ bazel --output_user_root=/home/bazel-results/cache build -c opt --cxxopt=--std=c++17 --config=android_arm64 --host_crosstool_top=@bazel_tools//tools/cpp:toolchain --define=build_with_mkl=true //tmp:tensorflowlite_flex --verbose_failures\r\n```\r\nproduces eventually:\r\n```\r\ntensorflow/core/kernels/mkl/mkl_avgpooling_op.cc:19:10: fatal error: dnnl.hpp: No such file or directory\r\n 19 | #include \"dnnl.hpp\"\r\n | ^~~~~~~~~~\r\ncompilation terminated.\r\nTarget //tmp:tensorflowlite_flex failed to build\r\nINFO: Elapsed time: 55.406s, Critical Path: 39.28s\r\nINFO: 776 processes: 50 internal, 726 local.\r\n```\r\n\r\n@terryheo, can you please take a look? Thanks.", "Hi @pkgoogle , @terryheo. \r\n\r\nJust checking if you have any updates on this issue.\r\n\r\nThanks." ]

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[ "@AyushShahh Could you please make sure to follow the steps mentioned [here](https://www.tensorflow.org/install/source_windows). FYI, GPU support on native-Windows is only available for 2.10 or earlier versions, starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in [WSL2](https://www.tensorflow.org/install/pip#windows-wsl2) or use tensorflow-cpu with TensorFlow-DirectML-Plugin.\r\n\r\nThank you! ", "I followed all the steps and I am not building the tensorflow-gpu, I am building the normal version only", "@mraunak , Could you please take a look into this. Thanks!", "Hi @AyushShahh, --config=mkl is not supported on Windows, if you remove that, it should work.\r\nPlease let me know if you face any further issues. Moreover, for more information regarding config and inputs to the compiler or linker, you can refer to this link https://github.com/tensorflow/tensorflow/blob/master/.bazelrc", "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/61661\">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/61661\">No</a>\n" ]

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[ "@jpienaar I did my best to address your comments. Let me know if there's anything else you'd like me to take care of.", "Hi @rafaelubalmw Can you please resolve conflicts? Thank you!\r\n", "This PR is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.", "Hi @rafaelubalmw Can you please resolve conflicts? Thank you!" ]

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[ "@kvnsng Could you please confirm the python version you are using?\r\nPlease make sure to use the [compatible](https://www.tensorflow.org/install/source#ubuntu) versions when you are upgrading TF version. \r\nIn order to expedite the trouble-shooting process, please provide a code snippet to reproduce the issue reported here. Thank you!", "@sushreebarsa `tensorflow==2.4.1` was used with `python 3.8` and `tensorflow==2.13.0` was with `python 3.10`. I used a docker image from tensorflow dockerhub, so I imagine it all had the correct TF versions.\r\n\r\nI'll try to prep a small code snippet that could reproduce the issue. Thanks!", "@kvnsng Is there any update on this issue?\r\nThank you!", "@sushreebarsa apologies for the delay but work has been crazy. I'll work on getting a code snippet together by the end of this week. Thanks!", "Hi @kvnsng ,\r\n\r\nThe version difference is huge from 2.4 to 2.14, many things have changed since then, it is difficult to point to the specific change without any reproducible code.\r\n\r\nIf you are not able to provide the reproducible code, I would suggest you to go through our release notes https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md which could help you to identify the changes made.\r\n\r\nIf you have managed to identify the source file of the module you are using, you can check the commit history to identify the changes made.", "@sachinprasadhs \r\n\r\nI tried to recreate the error by writing sample codes, but have not been able to. I can't share the full code due to legal reasons. I'll go ahead and close this since I can't provide a reproducible code.", "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/61659\">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/61659\">No</a>\n" ]

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[ "The warning message, is a strong indication that the Lambda layer should be rewritten as a subclassed Layer, suggests that there might be an issue with a Lambda layer in your code. Try rewriting the Lambda layer using the tf.keras.layers.Layer subclassing approach instead of using a Lambda layer directly.", "@Ella-Adu,\r\ntf.keras.Lambda: Note that if variables are involved in the layer created by this method, the variable will not be automatically added to the variable set for gradient calculation. Therefore, if there are parameters to be trained in the user-defined layer, it is recommended to customize the model layer based on the base class.\r\n\r\n```\r\nweights = tf.Variable(tf.random.normal((4, 2)), name='w')\r\nbias = tf.ones((1, 2), name='b')\r\nprint(bias)\r\nx_input = tf.range(12.).numpy().reshape(-1, 4)\r\n\r\n# lambda custom layer\r\nmylayer1 = tf.keras.layers.Lambda(lambda x: tf.add(tf.matmul(x, weights),\r\n bias), name='lambda1')\r\nmylayer1(x_input)\r\n\r\ntf.Tensor([[1. 1.]], shape=(1, 2), dtype=float32)\r\n```\r\nAlso please have a look at this [blog](https://programming.vip/docs/day-6-tensorflow2-model-subclassing-api.html) for reference. Thank 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/61658\">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/61658\">No</a>\n" ]

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[ "Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA).\n\nView this [failed invocation](https://github.com/tensorflow/tensorflow/pull/61657/checks?check_run_id=16069742225) of the CLA check for more information.\n\nFor the most up to date status, view the checks section at the bottom of the pull request." ]

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[ "Hi @dsnsabari ,\r\n\r\nThe warnings related to grappler observed in older versions.These are warnings only and hence code execution and predictions not affected. Please find relevant issue [here](https://github.com/tensorflow/tensorflow/issues/50575) where the issue might have fixed with latest versions.\r\n\r\nAs there is no minimal code snippet I can't able to test it. Could you please provide minimal code snippet to reproduce the issue or test your model with latest TF versions preferably 2.12v or higher and let us know if same warnings still persists.\r\n\r\nThanks!\r\n\r\n", "hi @SuryanarayanaY , Still the error exists in the latest TensorFlow version. Did you check his comment? \r\n\r\nhttps://github.com/tensorflow/tensorflow/issues/50575#issuecomment-1670905587\r\n", "Hi @dsnsabari ,\r\n\r\nCould you please submit a minimal code snippet to replicate the reported behaviour. Thanks!", "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/61656\">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/61656\">No</a>\n" ]

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[ "I was able to reproduce this issue with TF2.13 and master branch as well. \r\n\r\n@pkgoogle Could you please check this issue?\r\n\r\nThanks.\r\n\r\n<img width=\"562\" alt=\"Screenshot 2023-08-24 at 11 42 14 AM\" src=\"https://github.com/tensorflow/tensorflow/assets/118897289/22eac763-6f5e-43fa-aefe-0ea32d287dcf\">\r\n", "Hi @B-JackMao, \r\n\r\nI'm actually getting a different error:\r\n```\r\nINFO: Found applicable config definition build:dynamic_kernels in file /usr/local/google/home/xxxxxx/tensorflow/.bazelrc: --define=dynamic_loaded_kernels=true --copt=-DAUTOLOAD_DYNAMIC_KERNELS\r\nERROR: /usr/local/google/home/xxxxxx/tensorflow/tensorflow/lite/java/BUILD:297:16: While resolving toolchains for target //tensorflow/lite/java:tensorflowlite_gpu_impl: no matching toolchains found for types @bazel_tools//tools/android:sdk_toolchain_type\r\nERROR: Analysis of target '//tensorflow/lite/java:tensorflow-lite-gpu' failed; build aborted: \r\nINFO: Elapsed time: 24.188s\r\nINFO: 0 processes.\r\nFAILED: Build did NOT complete successfully (51 packages loaded, 242 targets configured)\r\n```\r\ncan you please provide exact steps. I.e. are you using the configure script? If so, what options did you specify? Are you following this [resource](https://www.tensorflow.org/lite/android/lite_build) at all? or any other resource? Are you using the docker file or something else?\r\n\r\nPreferably write the steps as you would edit a Dockerfile or a shell script.\r\nexample:\r\n```sh\r\ngit clone https://github.com/tensorflow/tensorflow.git\r\ncd tensorflow\r\ngit switch r2.13\r\ngit pull\r\nbazel build -c opt --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a --host_crosstool_top=@bazel_tools//tools/cpp:toolchain //tensorflow/lite/java:tensorflow-lite-gpu\r\n```", "# install python and prerequisites sudo apt install python-dev python-pip pip install -U --user pip six numpy wheel mock pip install -U --user keras_applications==1.0.6 --no-deps pip install -U --user keras_preprocessing==1.0.5 --no-deps # install openjdk-8 sudo apt-get install openjdk-8-jdk \r\n\r\n\r\n# install bazel 6.1.0\r\n# install the prerequisites sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python chmod +x bazel-6.1.0-installer-linux-x86_64.sh ./bazel-6.1.0-installer-linux-x86_64.sh --user # setup environment export PATH=\"$PATH:$HOME/bin\"\r\n\r\n\r\n##Android\r\nmkdir ~/Android cd Android #NDK use ndk r19c unzip android-ndk-r19c-linux-x86_64.zip mkdir Sdk mv android-ndk-r19c Sdk/ndk-bundle #SDK wget https://dl.google.com/android/repository/sdk-tools-linux-4333796.zip unzip sdk-tools-linux-4333796.zip mv tools/ Sdk/ # Platform tools wget https://dl.google.com/android/repository/platform-tools-latest-linux.zip unzip platform-tools-latest-linux.zip mv platform-tools Sdk/ # Using sdkmanager to install tools cd Sdk chmod a+x tools/bin/sdkmanager ./tools/bin/sdkmanager \"platform-tools\" \"platforms;android-27\" \"platforms;android-28\" \"platforms;android-29\" \"platforms;android-30\" \"build-tools;30.0.0\" \"build-tools;29.0.3\" \r\n\r\n\r\n\r\n download tensorflow code git clone https://github.com/tensorflow/tensorflow.git cd tensorflow ./configure\r\n\r\n\r\nabout\"y/N\",only \"WORKSPACES\"choose y,other choose \"N\",Choose the default configuration for the rest\r\n\r\n\r\nrun command “bazel build -c opt --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a ***@***.***_tools//tools/cpp:toolchain //tensorflow/lite/java:tensorflow-lite-gpu” and want to build \"tensorflow-lite-gpu.aar\" \r\n\r\n\r\n\r\n\r\nand error occurred.\r\n\r\n\r\n\r\n\r\n\r\n\r\n------------------&nbsp;原始邮件&nbsp;------------------\r\n发件人: ***@***.***&gt;; \r\n发送时间: 2023年8月25日(星期五) 凌晨1:31\r\n收件人: ***@***.***&gt;; \r\n抄送: ***@***.***&gt;; ***@***.***&gt;; \r\n主题: Re: [tensorflow/tensorflow] Compiling src/amalgam/gen/neonfp16arith.c failed: (Exit 70): clang failed: error executing command (from target @XNNPACK//:neonfp16arith_amalgam_microkernels) external/androidndk/ndk/toolchains/llvm/prebuilt/linux-x86_64/bin/clang &#39;-D__ANDROID_API__=26&#39; -isystemexternal/androidndk/ndk/sysroot/usr/include/arm-linux-androideabi -target ... (remaining 71 arguments skipped) (Issue #61655)\r\n\r\n\r\n\r\n\r\n\r\n \r\nHi @B-JackMao,\r\n \r\nI'm actually getting a different error:\r\n INFO: Found applicable config definition build:dynamic_kernels in file /usr/local/google/home/xxxxxx/tensorflow/.bazelrc: --define=dynamic_loaded_kernels=true --copt=-DAUTOLOAD_DYNAMIC_KERNELS ERROR: /usr/local/google/home/xxxxxx/tensorflow/tensorflow/lite/java/BUILD:297:16: While resolving toolchains for target //tensorflow/lite/java:tensorflowlite_gpu_impl: no matching toolchains found for types @bazel_tools//tools/android:sdk_toolchain_type ERROR: Analysis of target '//tensorflow/lite/java:tensorflow-lite-gpu' failed; build aborted: INFO: Elapsed time: 24.188s INFO: 0 processes. FAILED: Build did NOT complete successfully (51 packages loaded, 242 targets configured) \r\ncan you please provide exact steps. I.e. are you using the configure script? If so, what options did you specify? Are you following this resource at all? or any other resource? Are you using the docker file or something else?\r\n \r\nPreferably write the steps as you would edit a Dockerfile or a shell script.\r\n example:\r\n git clone https://github.com/tensorflow/tensorflow.git cd tensorflow git switch r2.13 git pull bazel build -c opt --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a ***@***.***_tools//tools/cpp:toolchain //tensorflow/lite/java:tensorflow-lite-gpu\r\n \r\n—\r\nReply to this email directly, view it on GitHub, or unsubscribe.\r\nYou are receiving this because you were mentioned.Message ID: ***@***.***&gt;", "I am able to reproduce with the following modifications:\r\n\r\nSet API level = 30 when asked during configuration, the final command for reproducibility was:\r\n```sh\r\nbazel build -c opt --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a --host_crosstool_top=@bazel_tools//tools/cpp:toolchain //tensorflow/lite/java:tensorflow-lite-gpu\r\n```\r\n\r\n```sh\r\nERROR: /usr/local/google/home/xxxxxx/.cache/bazel/_bazel_xxxxxx/caf3a5af5fd2180c9e3e5a21b39f1c0d/external/XNNPACK/BUILD.bazel:3046:19: Compiling src/amalgam/gen/neonfp16arith.c failed: (Exit 70): clang failed: error executing command (from target @XNNPACK//:neonfp16arith_amalgam_microkernels) \r\n (cd /usr/local/google/home/xxxxxx/.cache/bazel/_bazel_xxxxxx/caf3a5af5fd2180c9e3e5a21b39f1c0d/execroot/org_tensorflow && \\\r\n exec env - \\\r\n ANDROID_BUILD_TOOLS_VERSION=30.0.3 \\\r\n ANDROID_NDK_API_LEVEL=26 \\\r\n ANDROID_NDK_HOME=/usr/local/google/home/xxxxxx/Android/Sdk/ndk/android-ndk-r19c \\\r\n ANDROID_SDK_API_LEVEL=30 \\\r\n ANDROID_SDK_HOME=/usr/local/google/home/xxxxxx/Android/Sdk \\\r\n LD_LIBRARY_PATH=/usr/lib/mesa-diverted/x86_64-linux-gnu:/usr/lib/x86_64-linux-gnu/mesa:/usr/lib/x86_64-linux-gnu/dri:/usr/lib/x86_64-linux-gnu/gallium-pipe \\\r\n PATH=/usr/local/google/home/xxxxxx/.cache/bazelisk/downloads/bazelbuild/bazel-6.1.0-linux-x86_64/bin:/usr/local/google/home/xxxxxxx/miniconda3/envs/61655/bin:/usr/local/google/home/xxxxxx/miniconda3/condabin:/usr/local/google/home/xxxxxx/.local/bin:/usr/lib/google-golang/bin:/usr/local/buildtools/java/jdk/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/snap/bin \\\r\n PWD=/proc/self/cwd \\\r\n PYTHON_BIN_PATH=/usr/local/google/home/xxxxxx/miniconda3/envs/61655/bin/python3 \\\r\n PYTHON_LIB_PATH=/usr/local/google/home/xxxxxxx/miniconda3/envs/61655/lib/python3.11/site-packages \\\r\n TF2_BEHAVIOR=1 \\\r\n external/androidndk/ndk/toolchains/llvm/prebuilt/linux-x86_64/bin/clang '-D__ANDROID_API__=26' -isystemexternal/androidndk/ndk/sysroot/usr/include/arm-linux-androideabi -target armv7-none-linux-androideabi '-march=armv7-a' '-mfloat-abi=softfp' '-mfpu=vfpv3-d16' -gcc-toolchain external/androidndk/ndk/toolchains/arm-linux-androideabi-4.9/prebuilt/linux-x86_64 -fpic -no-canonical-prefixes -Wno-invalid-command-line-argument -Wno-unused-command-line-argument -funwind-tables -fstack-protector-strong -fno-addrsig '-Werror=return-type' '-Werror=int-to-pointer-cast' '-Werror=pointer-to-int-cast' '-Werror=implicit-function-declaration' -mthumb -Os -g -DNDEBUG -MD -MF bazel-out/android-armeabi-v7a-opt/bin/external/XNNPACK/_objs/neonfp16arith_amalgam_microkernels/neonfp16arith.pic.d '-frandom-seed=bazel-out/android-armeabi-v7a-opt/bin/external/XNNPACK/_objs/neonfp16arith_amalgam_microkernels/neonfp16arith.pic.o' -fPIC '-DBAZEL_CURRENT_REPOSITORY=\"XNNPACK\"' -iquote external/XNNPACK -iquote bazel-out/android-armeabi-v7a-opt/bin/external/XNNPACK -isystem external/XNNPACK/include -isystem bazel-out/android-armeabi-v7a-opt/bin/external/XNNPACK/include -isystem external/XNNPACK/src -isystem bazel-out/android-armeabi-v7a-opt/bin/external/XNNPACK/src -Wno-all -Wno-extra -Wno-deprecated -Wno-deprecated-declarations -Wno-ignored-attributes -Wno-array-bounds -Wunused-result '-Werror=unused-result' -Wswitch '-Werror=switch' '-Wno-error=unused-but-set-variable' -DAUTOLOAD_DYNAMIC_KERNELS -Iinclude -Isrc -marm '-march=armv8.2-a+fp16' '-mfpu=neon-fp-armv8' '-std=c99' -O2 '--sysroot=external/androidndk/ndk/platforms/android-26/arch-arm' -isystem external/androidndk/ndk/sources/cxx-stl/llvm-libc++/include -isystem external/androidndk/ndk/sources/cxx-stl/llvm-libc++abi/include -isystem external/androidndk/ndk/sources/android/support/include -isystemexternal/androidndk/ndk/sysroot/usr/include -c external/XNNPACK/src/amalgam/gen/neonfp16arith.c -o bazel-out/android-armeabi-v7a-opt/bin/external/XNNPACK/_objs/neonfp16arith_amalgam_microkernels/neonfp16arith.pic.o)\r\n# Configuration: ee5ef3675746c4253f216a2d59070e2657d7f9037448cc2d2289ec75605ec73c\r\n# Execution platform: @local_execution_config_platform//:platform\r\nwarning: unknown warning option '-Werror=unused-but-set-variable'; did you mean '-Werror=unused-const-variable'? [-Wunknown-warning-option]\r\nfatal error: error in backend: Cannot select: 0x65727a8: v8f16 = bitcast 0x656f438, external/XNNPACK/src/amalgam/gen/neonfp16arith.c:51:28\r\n 0x656f438: v8i16,ch = ARMISD::VLD1DUP<(load 2 from %ir.17)> 0x68b7628, 0x6572608, Constant:i32<2>, external/XNNPACK/src/amalgam/gen/neonfp16arith.c:51:50\r\n 0x6572608: i32 = add nuw 0x656fcc0, Constant:i32<2>, external/XNNPACK/src/amalgam/gen/neonfp16arith.c:51:50\r\n 0x656fcc0: i32,ch = load<(load 4 from %fixed-stack.0, align 8)> 0x68b7628, FrameIndex:i32<-7>, undef:i32\r\n 0x656fc58: i32 = FrameIndex<-7>\r\n 0x656f778: i32 = undef\r\n 0x65725a0: i32 = Constant<2>\r\n 0x65725a0: i32 = Constant<2>\r\nIn function: xnn_f16_avgpool_minmax_ukernel_9p8x__neonfp16arith_c8\r\nclang: error: clang frontend command failed with exit code 70 (use -v to see invocation)\r\nAndroid (5058415 based on r339409) clang version 8.0.2 (https://android.googlesource.com/toolchain/clang 40173bab62ec746213857d083c0e8b0abb568790) (https://android.googlesource.com/toolchain/llvm 7a6618d69e7e8111e1d49dc9e7813767c5ca756a) (based on LLVM 8.0.2svn)\r\nTarget: armv7-none-linux-android\r\nThread model: posix\r\nInstalledDir: external/androidndk/ndk/toolchains/llvm/prebuilt/linux-x86_64/bin\r\nclang: note: diagnostic msg: PLEASE submit a bug report to https://bugs.llvm.org/ and include the crash backtrace, preprocessed source, and associated run script.\r\nclang: note: diagnostic msg: \r\n********************\r\n\r\nPLEASE ATTACH THE FOLLOWING FILES TO THE BUG REPORT:\r\nPreprocessed source(s) and associated run script(s) are located at:\r\nclang: note: diagnostic msg: /tmp/neonfp16arith-2b5d8a.c\r\nclang: note: diagnostic msg: /tmp/neonfp16arith-2b5d8a.sh\r\nclang: note: diagnostic msg: \r\n\r\n********************\r\nTarget //tensorflow/lite/java:tensorflow-lite-gpu failed to build\r\nINFO: Elapsed time: 3.274s, Critical Path: 2.56s\r\nINFO: 288 processes: 175 internal, 113 local.\r\nFAILED: Build did NOT complete successfully\r\n```\r\n\r\nHi @miaout17, can you please take a look? Thanks." ]

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[ "Hi @SichangHe, Can you provide more detailed instructions on how to replicate? I have created the model with your scripts but when I attempt to run the Android Studio Project for the client I get this issue:\r\n\r\n\r\n\r\nI am unfamiliar with Flutter/Dart so I'm probably just missing some steps, please let me know so that we may be able to reproduce your issue effectively. The more details you include the less back and forth we have to go through to reproduce your issue. Thanks for your help!", "Hi @pkgoogle.\r\n\r\nGlad that the model generation script worked for you.\r\n\r\nI will create a repository without Flutter to help you reproduce this issue.\r\n", "I've created https://github.com/SichangHe/reproduce_tensorflow_tensorflow_issue_61654, but it doesn't crash… I'm not sure why.", "The original app did not crash neither during my testing earlier today. I will talk to my colleague.", "@SichangHe, Thanks for checking, hope it helps!", "My colleague reproduced it again.\r\n\r\nIn the log, it seems that the sequence is `fit - evaluate - fit - eval… crash`. I will make it so that one could alter fit & evaluate so maybe we would be able to reproduce it.\r\n\r\nAnother take is to use the real data we used, but I'm not sure that is really relevant.", "I cycled through fitting and evaluation and used the data lead to the previous crash but it still didn't crash… I also cannot reproduce the crash using our app on my device any more, but my colleague still get crashes using our app on his device.\r\n\r\nAny ideas why this inconsistency happens and how to help reproduce the crash?", "Hi @SichangHe, as you can imagine this is a tough situation haha. What device is your colleague using? Can you include logging for your app and give us the crash report? That is probably the best way to move forward. Thank you for your help.", "@Beilong-Tang, could you provide the above information?", "Unfortunately, we could not reproduce this issue any more. So, I'm closing this.\r\n\r\n@pkgoogle, thanks for sticking around and helping!" ]

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[ "@dmc1778,\r\nI was able to reproduce the issue on colab using TF v2.12, 2.13, tf-nightly. Please find the attached [gist](https://colab.research.google.com/gist/tilakrayal/9f8239ce2a78438cb1af73973f495bb6/untitled1332.ipynb).\r\n\r\nSince Segmentation faults can be considered as potential security vulnerabilities please read [SECURITY.md](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) and report them through proper channel as mentioned in SECURITY.md. If you want to stick to a specific version then please follow [this](https://github.com/tensorflow/tensorflow/blob/master/README.md#patching-guidelines) and create your own patch to resolve such issues.\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/61653\">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/61653\">No</a>\n" ]

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[ "Hi @dmc1778 ,\r\n\r\nI have replicated the reported behaviour with Tf2.13v and tf-nightly also. Attached screenshot below for reference.\r\n\r\n<img width=\"1497\" alt=\"Screenshot 2023-08-22 at 4 02 45 PM\" src=\"https://github.com/tensorflow/tensorflow/assets/116063290/0d6acdef-55af-4e3b-bd0d-f71b10390c8c\">\r\n\r\nPlease report security issues using the proper channels as mentioned in [SECURITY.md](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) .\r\n" ]

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[ "@Gadrawingz For setting up the TF and installing the build tools to configure your development environment, please follow these steps as mentioned [here](https://www.tensorflow.org/install/source#setup_for_linux_and_macos). Thank 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/61651\">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/61651\">No</a>\n" ]

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[ "NOTE: \r\nWhen I downgraded tf from 2.13.0 to 2.12.0, the code worked as expected.\r\n\r\nThe output with tf 2.12.0. The final decoder layer is outputting values [0.5, 0.5, 0.5] as expected.\r\n\r\n```\r\nPython 3.8.17 (default, Jul 5 2023, 15:35:58) \r\n[Clang 14.0.6 ]\r\nPython Platform: macOS-13.4-arm64-arm-64bit\r\nTensor Flow Version: 2.12.0\r\nGPU is NOT AVAILABLE\r\n2023-08-21 00:18:53.489119: W tensorflow/tsl/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\r\n1/1 [==============================] - 0s 25ms/step\r\n[[0.5 0.5 0.5]]\r\n```", "Hi @therealsachin ,\r\n\r\nI have tested the provided code with Tf2.13v on both Linux and Macos and both are generating same output for me.\r\n\r\nPlease refer the result on colab [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/fea0b501ffcac2bc214e59a405cfbd48/61650_linux-tf2-13v.ipynb#scrollTo=NEyqZ0JD0pxk).\r\n\r\nPlease refer the attached logs on Macos.\r\n\r\n```\r\n(tf-metal) suryanarayanay-macbookpro:Downloads suryanarayanay$ python 61650_macos.py\r\nPython 3.9.16 (main, Mar 8 2023, 04:29:24) \r\n[Clang 14.0.6 ]\r\nPython Platform: macOS-13.5-arm64-arm-64bit\r\nTensor Flow Version: 2.13.0\r\nGPU is available\r\nMetal device set to: Apple M1 Pro\r\n\r\nsystemMemory: 16.00 GB\r\nmaxCacheSize: 5.33 GB\r\n\r\n1/1 [==============================] - 0s 320ms/step\r\n[[0.5 0.5 0.5]]\r\n(tf-metal) suryanarayanay-macbookpro:Downloads suryanarayanay$ python 61650_macos.py\r\nPython 3.9.16 (main, Mar 8 2023, 04:29:24) \r\n[Clang 14.0.6 ]\r\nPython Platform: macOS-13.5-arm64-arm-64bit\r\nTensor Flow Version: 2.13.0\r\nGPU is available\r\nMetal device set to: Apple M1 Pro\r\n\r\nsystemMemory: 16.00 GB\r\nmaxCacheSize: 5.33 GB\r\n\r\n1/1 [==============================] - 0s 50ms/step\r\n[[0.5 0.5 0.5]]\r\n(tf-metal) suryanarayanay-macbookpro:Downloads suryanarayanay$ cat 61650_macos.py \r\n# -*- coding: utf-8 -*-\r\n\"\"\"61650_macos(TF2.13v).ipynb\r\n\r\nAutomatically generated by Colaboratory.\r\n\r\nOriginal file is located at\r\n https://colab.research.google.com/drive/1pHTvZjMFeqpRTuX_ShlFwGfDOUQl3AId?resourcekey=0-0g-rwvb7Fa9-4Kuw0eIlRA\r\n\"\"\"\r\n\r\n# !pip install tensorflow==2.13.*\r\n\r\nimport tensorflow as tf\r\nimport tensorflow.keras\r\nimport tensorflow as tf\r\nimport platform\r\nimport sys\r\nfrom tensorflow.keras.layers import Input, Dense, Layer\r\nfrom tensorflow.keras.models import Model\r\n\r\n# Print versions:\r\nprint(f\"Python {sys.version}\")\r\nprint(f\"Python Platform: {platform.platform()}\")\r\nprint(f\"Tensor Flow Version: {tf.__version__}\")\r\ngpu = len(tf.config.list_physical_devices('GPU'))>0\r\nprint(\"GPU is\", \"available\" if gpu else \"NOT AVAILABLE\")\r\n\r\n# Setup input\r\nimport numpy as np\r\nX_check = np.array([[1, 0, 0]])\r\n\r\n# Setup autoencoder model\r\ninput_layer = Input(shape=(X_check.shape[1]))\r\nbottleneck = Dense(2, activation='relu', name='bottleneck')(input_layer)\r\noutput = Dense(X_check.shape[1], activation='sigmoid', name='output')(bottleneck)\r\nautoencoder = Model(input_layer, output)\r\n\r\n# Set encoder layer weights to all negative.\r\nlayer = autoencoder.layers[1]\r\nweights = np.array([[-1, -1],[-1, -1], [-1, -1]])\r\nbiases = np.array([0, 0])\r\nlayer.set_weights([weights, biases])\r\n\r\n# create encoder model.\r\nencoder = Model(input_layer, bottleneck)\r\n\r\n# create decoder model.\r\ndecoder_input = Input(shape=(2,), name='decoder_input')\r\ndecoder_layer = autoencoder.layers[-1]\r\ndecoder = Model(decoder_input, decoder_layer(decoder_input))\r\n\r\n# Run auto-encoder, with [1, 0, 0], since encoder has all negative weights,\r\n# and has 'relu' activation o/p of enocder should all be zeros. And that being\r\n# the input of next sigmod we should get output [0.5, 0.5, 0.5]\r\noutput_data = autoencoder.predict(X_check)\r\nprint(output_data)(tf-metal) suryanarayanay-macbookpro:Downloads suryanarayanay$ \r\n```", "Hi @SuryanarayanaY ,\r\n\r\nFYI. I am running on Apple M2 Max, 64 GB, macOS Ventura Version 13.4 (22F66).\r\n\r\nI can replicate the issue on my machine. Is there anything that I can do to debug this more? Like, run all tests locally and see if any of the tests fails? Or do something else.\r\n\r\nWhen I set to eager execution to true the bug does not manifest. So I am guessing this has something to do with the execution graph optimization. ", "Hi @therealsachin ,\r\n\r\nI have disable V2 behaviour using `tf.compat.v1.disable_v2_behavior()`to disable eager execution and added `print(tf.executing_eagerly())` at last. Then executed the code again it's not replicating reported behaviour.Please refer attached logs.\r\n\r\n```\r\n(base) suryanarayanay-macbookpro:Downloads suryanarayanay$ python 61650_graph_mode_macos_tf2_13v.py\r\nWARNING:tensorflow:From /Users/suryanarayanay/miniconda/lib/python3.10/site-packages/tensorflow/python/compat/v2_compat.py:107: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\r\nInstructions for updating:\r\nnon-resource variables are not supported in the long term\r\nPython 3.10.9 (main, Jan 11 2023, 09:18:18) [Clang 14.0.6 ]\r\nPython Platform: macOS-13.5.1-arm64-arm-64bit\r\nTensor Flow Version: 2.13.0\r\nGPU is available\r\nMetal device set to: Apple M1 Pro\r\n\r\nsystemMemory: 16.00 GB\r\nmaxCacheSize: 5.33 GB\r\n\r\n2023-09-06 14:54:16.368497: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:303] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.\r\n2023-09-06 14:54:16.368700: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:269] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)\r\n2023-09-06 14:54:16.371797: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:375] MLIR V1 optimization pass is not enabled\r\n2023-09-06 14:54:16.379867: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\r\n2023-09-06 14:54:16.397685: W tensorflow/c/c_api.cc:304] Operation '{name:'output/kernel/Assign' id:33 op device:{requested: '', assigned: ''} def:{{{node output/kernel/Assign}} = AssignVariableOp[_has_manual_control_dependencies=true, dtype=DT_FLOAT, validate_shape=false](output/kernel, output/kernel/Initializer/random_uniform)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.\r\n2023-09-06 14:54:16.398514: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\r\n2023-09-06 14:54:16.469451: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\r\n/Users/suryanarayanay/miniconda/lib/python3.10/site-packages/keras/src/engine/training_v1.py:2359: UserWarning: `Model.state_updates` will be removed in a future version. This property should not be used in TensorFlow 2.0, as `updates` are applied automatically.\r\n updates=self.state_updates,\r\n2023-09-06 14:54:16.478393: W tensorflow/c/c_api.cc:304] Operation '{name:'output/Sigmoid' id:44 op device:{requested: '', assigned: ''} def:{{{node output/Sigmoid}} = Sigmoid[T=DT_FLOAT, _has_manual_control_dependencies=true](output/BiasAdd)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.\r\n2023-09-06 14:54:16.479109: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.\r\n[[0.5 0.5 0.5]]\r\nFalse\r\n(base) suryanarayanay-macbookpro:Downloads suryanarayanay$ \r\n```\r\nThe bug doesn't manifest without Eager execution also. Did you tried with any alternate method? \r\n\r\nThanks!", "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/61650\">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/61650\">No</a>\n" ]

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[ "@junaidjawaid1,\r\nHave you installed CUDA from the [official site](https://developer.nvidia.com/cuda-downloads)? And have you installed the right version? The [current one is 11.8](https://www.tensorflow.org/install/source#gpu).\r\n\r\nAlso you are trying with tensorflow v2.1 which is a pretty older version. It's unlikely for TF 2.1 version to receive any bug fixes except when we have security patches. There is a high possibility that this was fixed with later TF versions. Perhaps you can use the latest tf versions for your case. \r\nhttps://www.tensorflow.org/install\r\nThank you!", "> \r\n\r\nThank you so much for the response. I am using v2.1 cause LMS support is only available with this version. If you can guide me regarding memory swapping in the latest versions that would really helpful.\r\nThank you.", "@junaidjawaid1,\r\nTensorflow v2.1 is compatible with python 2.7, 3.5-3.7, compile GCC 7.3.1, Bazel 0.27.1, CUDA 7.6, cuDNN 10.1. \r\nhttps://www.tensorflow.org/install/source#gpu\r\nAlso as the error(ModuleNotFoundError: No module named 'nvidia') stated, this error occurred due to Nvidia and not from the tensorflow. Thank you!\r\n\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/61649\">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/61649\">No</a>\n", "> Are you satisfied with the resolution of your issue? [Yes](https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/61649) [No](https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/61649)\r\n\r\nyes, I am satisfied. Thank you all for your response." ]

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[ "Python 3.8 is no longer supported. You must use Python 3.9, 3.10 or 3.11.\r\nAlso you appear to be building as root. Don't do that.", "Please create a new environment and make sure Bazel and other dependencies are installed properly as per the tested build configuration mentioned below. \r\nhttps://www.tensorflow.org/install/source#cpu", "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/61648\">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/61648\">No</a>\n" ]

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[ "Hello, @wolfgang42! Could you please point here the page where the link didn't work for you so that we could fix it. Thank you!", "Some examples include https://www.tensorflow.org/ and https://www.tensorflow.org/js , but I didn’t do an exhaustive search.", "@wolfgang42 Thank you for your response!\r\nCould you please give the exact sorce file where you found this [link](https://www.tensorflow.org/static/en/site-assets/images/marketing/favicon.png) as it will be easier for us to clean up such broken links from website. Thank you! ", "If by “sorce file” you mean pages where you can “View source” and see the link:\r\n\r\n> Some examples include https://www.tensorflow.org/ and https://www.tensorflow.org/js\r\n\r\nAnd if you mean the file where this problem originates:\r\n\r\n> I can’t work out where the template for this lives\r\n", "Hi,\r\nIt is a TensorFlow logo which will be rendered in the website and below attached is the image.\r\n\r\n\r\n\r\nI don't see any issue here, feel free to close the issue. Thanks!\r\n", "I don’t know what that screenshot is of, but if you follow the [actual link](https://www.tensorflow.org/static/en/site-assets/images/marketing/favicon.png) as embedded in the page, you’ll find that it returns a 404." ]

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[ "Hi @dmc1778,\r\nI was able to reproduce the issue on colab using TF v2.13, tf-nightly. Please find the attached [gist](https://colab.sandbox.google.com/gist/Varsha-anjanappa/d8e29e7afd36fba18f4d1f168770b17c/61646.ipynb).\r\n\r\nSince Segmentation faults can be considered as potential security vulnerabilities please read [SECURITY.md](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) and report them through proper channel as mentioned in SECURITY.md.\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/61646\">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/61646\">No</a>\n" ]

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[ "1.Convert your TensorFlow checkpoint files to a SavedModel format. This is typically done using the tf.saved_model.save function. Here's an example:\r\n\r\nimport tensorflow as tf\r\n\r\n# Load the model architecture and checkpoint\r\nmodel = ... # Load or define your model here\r\ncheckpoint_path = 'path/to/your/model.ckpt'\r\ncheckpoint = tf.train.Checkpoint(model=model)\r\ncheckpoint.restore(checkpoint_path).expect_partial()\r\n\r\n# Save the model in SavedModel format\r\nsaved_model_path = 'path/to/save/saved_model'\r\ntf.saved_model.save(model, saved_model_path)\r\n\r\n2.After exporting the model to the SavedModel format, you can then use the TensorFlow Lite Converter (tf.lite.TFLiteConverter) to convert the SavedModel to TFLite format:\r\n\r\n# Convert SavedModel to TFLite\r\ntflite_converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_path)\r\ntflite_model = tflite_converter.convert()\r\n\r\n3.Finally, save the TFLite model to a .tflite file:\r\n\r\ntflite_model_path = 'path/to/save/model.tflite'\r\nwith open(tflite_model_path, 'wb') as f:\r\n f.write(tflite_model)\r\n\r\n\r\n", "Hi @md-rifatkhan \r\n\r\nAs @Sourabh20022002 suggested, we need to save the checkpoints in SavedModel format and convert it to the TFLite model.\r\n\r\nIn addition to that, you can also use concrete functions to convert into TFLite model once you load the checkpoints in TF Model.\r\n\r\nPlease check these [examples](https://www.tensorflow.org/lite/models/convert/convert_models#convert_a_savedmodel_recommended_) for both the cases.\r\n\r\nThanks.\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/61645\">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/61645\">No</a>\n", "> How can I convert ckpt file to TF Lite, while I've only .ckpt file. No meta-file present\r\n\r\nThe convert can be achieved? I tried the metod, but still exists warning\r\n\r\nWARNING:tensorflow:Skipping full serialization of Keras layer <mlp_test.MLP object at 0x7faed0788f10>, because it is not built." ]

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[ "Hi @agkphysics ,\r\n\r\nThanks for reporting this. Yes I have tested the API **`tf.image.crop_to_bounding_box`** with all `tf.dtypes` `tf.uint8,tf.uint16,tf.uint32,tf.uint64,tf.int32,tf.int64, tf.float32, tf.float64,tf.bfloat16,tf.float16`\r\n\r\nOnly `tf.int32` is acceptable dtype for the arguments `offset_height, offset_width, target_height, target_width`. This is not documented well.\r\n\r\nAlso I have tested with **Python** `int` and `float` it's only works with python int but not float.\r\n\r\nAll the testing can be found in attached [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/953076ea1179b3db0a0ef0fc518a84a3/61644.ipynb) here.\r\n\r\nI may raise a PR for documenting this.\r\n\r\nThanks!" ]

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[ "@dmc1778 The issue is not getting replicated on colab using TF v2.13 and tf-nightly, please find the [gist](https://colab.research.google.com/gist/sushreebarsa/1ac4bd8ac80db3c5453fca1d9e36f14d/61643.ipynb) here. Thank you! ", "> @dmc1778 The issue is not getting replicated on colab using TF v2.13 and tf-nightly, please find the [gist](https://colab.research.google.com/gist/sushreebarsa/1ac4bd8ac80db3c5453fca1d9e36f14d/61643.ipynb) here. Thank you!\r\n\r\nThanks @sushreebarsa . My session on colab still getting crashed, probably due to check failure, please find the log message below:\r\n\r\n```\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Searching ['/root/.jupyter', '/root/.local/etc/jupyter', '/usr/etc/jupyter', '/usr/local/etc/jupyter', '/etc/jupyter'] for config files\",\"time\":\"2023-08-21T05:53:09.867Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Searching ['/root/.jupyter', '/root/.local/etc/jupyter', '/usr/etc/jupyter', '/usr/local/etc/jupyter', '/etc/jupyter'] for config files\",\"time\":\"2023-08-21T05:53:09.870Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Looking for jupyter_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.868Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.878 NotebookApp] Looking for jupyter_config in /usr/local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.883 NotebookApp] Looking for jupyter_config in /usr/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.883 NotebookApp] Looking for jupyter_config in /root/.local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.884 NotebookApp] Looking for jupyter_config in /root/.jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Looking for jupyter_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.871Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.869 NotebookApp] Looking for jupyter_config in /usr/local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.873Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.870 NotebookApp] Looking for jupyter_config in /usr/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.870 NotebookApp] Looking for jupyter_config in /root/.local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.871 NotebookApp] Looking for jupyter_config in /root/.jupyter\",\"time\":\"2023-08-21T05:53:09.883Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.871 NotebookApp] Looking for jupyter_notebook_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.883Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.875 NotebookApp] Loaded config file: 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server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret\",\"time\":\"2023-08-21T05:53:10.765Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Authentication of /metrics is OFF, since other authentication is disabled.\",\"time\":\"2023-08-21T05:53:10.771Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"google.colab serverextension initialized.\",\"time\":\"2023-08-21T05:53:10.836Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.878Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/local/etc/jupyter/jupyter_notebook_config.d/panel-client-jupyter.json\",\"time\":\"2023-08-21T05:53:10.880Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.880Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/root/.local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.883Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/root/.jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.884Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Writing notebook server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret\",\"time\":\"2023-08-21T05:53:10.893Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Authentication of /metrics is OFF, since other authentication is disabled.\",\"time\":\"2023-08-21T05:53:10.894Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"google.colab serverextension initialized.\",\"time\":\"2023-08-21T05:53:10.945Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Serving notebooks from local directory: /\",\"time\":\"2023-08-21T05:53:15.513Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Jupyter Notebook 6.5.5 is running at:\",\"time\":\"2023-08-21T05:53:15.514Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Serving notebooks from local directory: /\",\"time\":\"2023-08-21T05:53:15.521Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Jupyter Notebook 6.5.5 is running at:\",\"time\":\"2023-08-21T05:53:15.521Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"http://172.28.0.2:9000/\",\"time\":\"2023-08-21T05:53:15.521Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).\",\"time\":\"2023-08-21T05:53:15.522Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"http://172.28.0.12:9000/\",\"time\":\"2023-08-21T05:53:15.523Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).\",\"time\":\"2023-08-21T05:53:15.523Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Kernel started: 7be3ebb5-8079-41dd-a058-72f1e271f55f, name: python3\",\"time\":\"2023-08-21T05:53:32.402Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:38.426472: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\",\"time\":\"2023-08-21T05:53:38.426Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\",\"time\":\"2023-08-21T05:53:38.426Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:39.614903: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\",\"time\":\"2023-08-21T05:53:39.615Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:43.858531: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:43.858Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.410103: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.410Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.410567: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.410Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.413324: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.413Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.413957: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.414Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.414476: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.414Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.373843: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:48.374Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.380854: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:48.381Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.381791: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:48.381Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.382383: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:47] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\",\"time\":\"2023-08-21T05:53:48.382Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.382464: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1635] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 13664 MB memory: -> device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5\",\"time\":\"2023-08-21T05:53:48.382Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:53.331521: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:424] Loaded cuDNN version 8900\",\"time\":\"2023-08-21T05:53:53.331Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:53.332580: F tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:959] Check failed: cudnnSetPoolingNdDescriptor( handle_.get(), (pooling_descriptor.mode() == dnn::PoolingMode::kMaximum ? cudnn_max_pooling_mode : CUDNN_POOLING_AVERAGE_COUNT_EXCLUDE_PADDING), propagate_nans ? CUDNN_PROPAGATE_NAN : CUDNN_NOT_PROPAGATE_NAN, nd, shape.data(), padding.data(), strides.data()) == CUDNN_STATUS_SUCCESS (3 vs. 0)\",\"time\":\"2023-08-21T05:53:53.332Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"KernelRestarter: restarting kernel (1/5), keep random ports\",\"time\":\"2023-08-21T05:53:56.402Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"WARNING:root:kernel 7be3ebb5-8079-41dd-a058-72f1e271f55f restarted\",\"time\":\"2023-08-21T05:53:56.402Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:13.376745: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\",\"time\":\"2023-08-21T05:59:13.376Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\",\"time\":\"2023-08-21T05:59:13.377Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:16.272217: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\",\"time\":\"2023-08-21T05:59:16.272Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:33.700495: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:33.700Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:34.230690: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:34.230Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:34.231162: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:34.231Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:34.238614: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:34.238Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:34.242007: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:34.242Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:34.242295: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:34.242Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:35.389137: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:35.389Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:35.389644: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:35.390Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:35.390313: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:59:35.390Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:35.390544: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:47] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\",\"time\":\"2023-08-21T05:59:35.390Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:35.390622: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 13692 MB memory: -> device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5\",\"time\":\"2023-08-21T05:59:35.390Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:39.054266: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:432] Loaded cuDNN version 8900\",\"time\":\"2023-08-21T05:59:39.054Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:59:39.054436: F tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:983] Check failed: cudnnSetPoolingNdDescriptor( handle_.get(), (pooling_descriptor.mode() == dnn::PoolingMode::kMaximum ? cudnn_max_pooling_mode : CUDNN_POOLING_AVERAGE_COUNT_EXCLUDE_PADDING), propagate_nans ? CUDNN_PROPAGATE_NAN : CUDNN_NOT_PROPAGATE_NAN, nd, shape.data(), padding.data(), strides.data()) == CUDNN_STATUS_SUCCESS (3 vs. 0)\",\"time\":\"2023-08-21T05:59:39.055Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"KernelRestarter: restarting kernel (1/5), keep random ports\",\"time\":\"2023-08-21T05:59:41.410Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"WARNING:root:kernel 7be3ebb5-8079-41dd-a058-72f1e271f55f restarted\",\"time\":\"2023-08-21T05:59:41.410Z\",\"v\":0}\r\n```", "@dmc1778 That's an error that is being returned to the user instead of performing bad computations.\r\nCould you please report this in the proper channel as mentioned [here](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md). Thank you!", "@sushreebarsa , in the [last error log](https://github.com/tensorflow/tensorflow/issues/61643#issuecomment-1685700653) there is a CHECK failure, not an error that is being returned to the user.\r\n\r\nThe difference is that an error being returned to the user could be caught in a `try`-`catch`, would not crash the Python interpreter, etc, whereas the `CHECK` failure could result in a denial of service (which does not constitute a significant security issue, though it should be fixed)", "Hi @dmc1778 ,\r\n\r\nI have replicated the error with **GPU** environment. The behaviour is random. At first run the execution is success and when rerun it got the **CUDA_ERROR_ILLEGAL_ADDRESS** below.\r\n\r\n`E tensorflow/compiler/xla/stream_executor/cuda/cuda_event.cc:29] Error polling for event status: failed to query event: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered`\r\n\r\nAttached screenshot below for same. This needs to be fixed.\r\n\r\n\r\n<img width=\"1508\" alt=\"Screenshot 2023-08-23 at 5 34 45 PM\" src=\"https://github.com/tensorflow/tensorflow/assets/116063290/b58454d4-3303-4fd4-9481-13d73c5c8c26\">\r\n" ]

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[ "Hi @dmc1778,\r\n\r\nI have tested the code with tf version 2.12 and tf-nightly and its working fine by raising exception, please find the [gist](https://colab.sandbox.google.com/gist/Varsha-anjanappa/a9cbdf4d498596ff6c234d194ad7ae33/61642.ipynb) here. \r\n\r\nThank you!", "> \r\n\r\nThanks @Varsha-anjanappa. On my side (2.13.0):\r\n\r\n```\r\n2023-08-21 01:03:23.808421: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:432] Loaded cuDNN version 8600\r\n2023-08-21 01:03:23.808473: F tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:983] Check failed: cudnnSetPoolingNdDescriptor( handle_.get(), (pooling_descriptor.mode() == dnn::PoolingMode::kMaximum ? cudnn_max_pooling_mode : CUDNN_POOLING_AVERAGE_COUNT_EXCLUDE_PADDING), propagate_nans ? CUDNN_PROPAGATE_NAN : CUDNN_NOT_PROPAGATE_NAN, nd, shape.data(), padding.data(), strides.data()) == CUDNN_STATUS_SUCCESS (3 vs. 0)\r\nAborted\r\n```", "Hi @dmc1778 ,\r\n\r\nTested the code on colab with tf version 2.13 as well, it is working fine. Please find the [gist](https://colab.sandbox.google.com/gist/Varsha-anjanappa/7eb2785fcf9750d1bb628a877be1f624/61642_v2.ipynb).\r\n\r\nThank you!!\r\n\r\n", "> \r\n\r\nMy session on Colab is still crashing. Please find the attached snapshot:\r\n\r\n\r\nLog:\r\n\r\n```\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Searching ['/root/.jupyter', '/root/.local/etc/jupyter', '/usr/etc/jupyter', '/usr/local/etc/jupyter', '/etc/jupyter'] for config files\",\"time\":\"2023-08-21T05:53:09.867Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Searching ['/root/.jupyter', '/root/.local/etc/jupyter', '/usr/etc/jupyter', '/usr/local/etc/jupyter', '/etc/jupyter'] for config files\",\"time\":\"2023-08-21T05:53:09.870Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Looking for jupyter_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.868Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.878 NotebookApp] Looking for jupyter_config in /usr/local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.883 NotebookApp] Looking for jupyter_config in /usr/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.883 NotebookApp] Looking for jupyter_config in /root/.local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.884 NotebookApp] Looking for jupyter_config in /root/.jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.866 NotebookApp] Looking for jupyter_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.871Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.869 NotebookApp] Looking for jupyter_config in /usr/local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.873Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.870 NotebookApp] Looking for jupyter_config in /usr/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.870 NotebookApp] Looking for jupyter_config in /root/.local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.871 NotebookApp] Looking for jupyter_config in /root/.jupyter\",\"time\":\"2023-08-21T05:53:09.883Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.871 NotebookApp] Looking for jupyter_notebook_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.883Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.875 NotebookApp] Loaded config file: /etc/jupyter/jupyter_notebook_config.py\",\"time\":\"2023-08-21T05:53:09.884Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.876 NotebookApp] Looking for jupyter_notebook_config in /usr/local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.886Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.876 NotebookApp] Loaded config file: /usr/local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:09.886Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.877 NotebookApp] Looking for jupyter_notebook_config in /usr/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.887Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.877 NotebookApp] Looking for jupyter_notebook_config in /root/.local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.888Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.877 NotebookApp] Looking for jupyter_notebook_config in /root/.jupyter\",\"time\":\"2023-08-21T05:53:09.891Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.879 NotebookApp] Loaded config file: /root/.jupyter/jupyter_notebook_config.py\",\"time\":\"2023-08-21T05:53:09.891Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.889 NotebookApp] Looking for jupyter_notebook_config in /etc/jupyter\",\"time\":\"2023-08-21T05:53:09.889Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.889 NotebookApp] Loaded config file: /etc/jupyter/jupyter_notebook_config.py\",\"time\":\"2023-08-21T05:53:09.891Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.890 NotebookApp] Looking for jupyter_notebook_config in /usr/local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.892Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.890 NotebookApp] Loaded config file: /usr/local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:09.892Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.890 NotebookApp] Looking for jupyter_notebook_config in /usr/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.892Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.890 NotebookApp] Looking for jupyter_notebook_config in /root/.local/etc/jupyter\",\"time\":\"2023-08-21T05:53:09.892Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.890 NotebookApp] Looking for jupyter_notebook_config in /root/.jupyter\",\"time\":\"2023-08-21T05:53:09.892Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"[D 05:53:09.891 NotebookApp] Loaded config file: /root/.jupyter/jupyter_notebook_config.py\",\"time\":\"2023-08-21T05:53:09.895Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.735Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/local/etc/jupyter/jupyter_notebook_config.d/panel-client-jupyter.json\",\"time\":\"2023-08-21T05:53:10.745Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.745Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.746Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/root/.local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.747Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/root/.jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.747Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Writing notebook server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret\",\"time\":\"2023-08-21T05:53:10.765Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Authentication of /metrics is OFF, since other authentication is disabled.\",\"time\":\"2023-08-21T05:53:10.771Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"google.colab serverextension initialized.\",\"time\":\"2023-08-21T05:53:10.836Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.878Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/local/etc/jupyter/jupyter_notebook_config.d/panel-client-jupyter.json\",\"time\":\"2023-08-21T05:53:10.880Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.880Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/usr/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.882Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/root/.local/etc/jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.883Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\" \\t/root/.jupyter/jupyter_notebook_config.json\",\"time\":\"2023-08-21T05:53:10.884Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Writing notebook server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret\",\"time\":\"2023-08-21T05:53:10.893Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Authentication of /metrics is OFF, since other authentication is disabled.\",\"time\":\"2023-08-21T05:53:10.894Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"google.colab serverextension initialized.\",\"time\":\"2023-08-21T05:53:10.945Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Serving notebooks from local directory: /\",\"time\":\"2023-08-21T05:53:15.513Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Jupyter Notebook 6.5.5 is running at:\",\"time\":\"2023-08-21T05:53:15.514Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Serving notebooks from local directory: /\",\"time\":\"2023-08-21T05:53:15.521Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Jupyter Notebook 6.5.5 is running at:\",\"time\":\"2023-08-21T05:53:15.521Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"http://172.28.0.2:9000/\",\"time\":\"2023-08-21T05:53:15.521Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).\",\"time\":\"2023-08-21T05:53:15.522Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"http://172.28.0.12:9000/\",\"time\":\"2023-08-21T05:53:15.523Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).\",\"time\":\"2023-08-21T05:53:15.523Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"Kernel started: 7be3ebb5-8079-41dd-a058-72f1e271f55f, name: python3\",\"time\":\"2023-08-21T05:53:32.402Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:38.426472: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\",\"time\":\"2023-08-21T05:53:38.426Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\",\"time\":\"2023-08-21T05:53:38.426Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:39.614903: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\",\"time\":\"2023-08-21T05:53:39.615Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:43.858531: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:43.858Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.410103: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.410Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.410567: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.410Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.413324: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.413Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.413957: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.414Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:44.414476: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:44.414Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.373843: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:48.374Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.380854: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:48.381Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.381791: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:996] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\",\"time\":\"2023-08-21T05:53:48.381Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.382383: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:47] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\",\"time\":\"2023-08-21T05:53:48.382Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:48.382464: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1635] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 13664 MB memory: -> device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5\",\"time\":\"2023-08-21T05:53:48.382Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:53.331521: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:424] Loaded cuDNN version 8900\",\"time\":\"2023-08-21T05:53:53.331Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"2023-08-21 05:53:53.332580: F tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:959] Check failed: cudnnSetPoolingNdDescriptor( handle_.get(), (pooling_descriptor.mode() == dnn::PoolingMode::kMaximum ? cudnn_max_pooling_mode : CUDNN_POOLING_AVERAGE_COUNT_EXCLUDE_PADDING), propagate_nans ? CUDNN_PROPAGATE_NAN : CUDNN_NOT_PROPAGATE_NAN, nd, shape.data(), padding.data(), strides.data()) == CUDNN_STATUS_SUCCESS (3 vs. 0)\",\"time\":\"2023-08-21T05:53:53.332Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":30,\"msg\":\"KernelRestarter: restarting kernel (1/5), keep random ports\",\"time\":\"2023-08-21T05:53:56.402Z\",\"v\":0}\r\n{\"pid\":7,\"type\":\"jupyter\",\"level\":40,\"msg\":\"WARNING:root:kernel 7be3ebb5-8079-41dd-a058-72f1e271f55f restarted\",\"time\":\"2023-08-21T05:53:56.402Z\",\"v\":0}\r\n```", "Hi @dmc1778 ,\r\n\r\nAs you can see the below snapshot, It is executing as expected, please refer to the gist given [here](https://github.com/tensorflow/tensorflow/issues/61642#issuecomment-1685691779).\r\n\r\n\r\n\r\nThank you!!\r\n", "> Hi @dmc1778 ,\r\n> \r\n> As you can see the below snapshot, It is executing as expected, please refer to the gist given [here](https://github.com/tensorflow/tensorflow/issues/61642#issuecomment-1685691779).\r\n> \r\n> \r\n> \r\n> Thank you!!\r\n\r\nThis is a serious issue as we get different outputs. ", "Hi @dmc1778 ,\r\n\r\nWith CPU runtime the code executes fine and attached [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/267620ee9839af8f75f15797c51356a4/61642_cpu.ipynb) for reference.\r\n\r\nWith GPU runtime check fail followed by crash happening. Attached screenshot for below.\r\n\r\n<img width=\"1506\" alt=\"Screenshot 2023-08-23 at 4 46 03 PM\" src=\"https://github.com/tensorflow/tensorflow/assets/116063290/6ff947dc-d562-44e9-b8bc-57e980fa6aef\">\r\n\r\n" ]

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[ "Hi, I don't work on tf data so I don't think I'm the right reviewer for this PR, could you please find a different reviewer? Thanks!", "Hi @aaudiber Can you please review this PR ? Thank you!", "@wilsingosti My proposed change does not remove the concept of elements. After my change, the note reads:\r\n\r\n> Note: Like other `Dataset` methods, prefetch operates on the elements of the input dataset. It has no concept of examples vs. batches. `examples.prefetch(2)` will prefetch 2 examples, while `examples.batch(20).prefetch(2)` will prefetch 40 examples (2 batches, of 20 examples each).\r\n\r\nStill includes the concept of elements, and in my opinion the wording is now clearer. However if you think the current wording is clearer please close my PR.", "@matangover You are right. Your proposed change does not remove the concept of elements. However, I think the current wording fine and I would like to keep it. Thanks for contributing." ]

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[ "Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA).\n\nView this [failed invocation](https://github.com/tensorflow/tensorflow/pull/61640/checks?check_run_id=16015812030) of the CLA check for more information.\n\nFor the most up to date status, view the checks section at the bottom of the pull request.", "Hi @cantonios Can you please review this PR ? Thank you!" ]

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[ "related to https://github.com/tensorflow/tensorflow/issues/60330", "@sachinprasadhs,\r\nI was able to reproduce the issue on tensorflow v2.12, v2.13 and tf-nightly. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/5ba9acb20cc199769dc8cc79ab685fe2/61639.ipynb).", "any updates? thanks" ]

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[ "@i-chaochen From https://github.com/tensorflow/tensorflow/pull/61397#discussion_r1276540276, a proper fix is to change the line as `min(static_cast<unsigned int>(blockDim.y), static_cast<unsigned int>(num_rows - blockIdx.y * blockDim.y));`. Can you test it?" ]

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[ "Hi @B-JackMao \r\n\r\nThe TF 2.4.0 is not being supported currently. Can you please check with latest stable version TF 2.13. with following configurations?\r\n\r\n```\r\nbuild --action_env ANDROID_NDK_HOME=\"/usr/local/android/android-ndk-r21e\"\r\nbuild --action_env ANDROID_NDK_API_LEVEL=\"26\"\r\nbuild --action_env ANDROID_BUILD_TOOLS_VERSION=\"30.0.3\"\r\nbuild --action_env ANDROID_SDK_API_LEVEL=\"30\"\r\nbuild --action_env ANDROID_SDK_HOME=\"/usr/local/android/android-sdk-linux\"\r\n```\r\n\r\nand run\r\n\r\n```\r\nbazel build -c opt --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a \\\r\n --host_crosstool_top=@bazel_tools//tools/cpp:toolchain \\\r\n --define=android_dexmerger_tool=d8_dexmerger \\\r\n --define=android_incremental_dexing_tool=d8_dexbuilder \\\r\n //tensorflow/lite/java:tensorflow-lite\r\n```\r\n\r\nThanks.\r\n\r\n", "OK,thanks.", "Hi @B-JackMao \r\n\r\nCan you please close this issue as it is being tracked in #61655?\r\n\r\nThanks.", "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/61635\">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/61635\">No</a>\n" ]

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[]

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[ "[tombstone_00.zip](https://github.com/tensorflow/tensorflow/files/12376746/tombstone_00.zip)\r\n", "@monsterzlz Could you please try to upgrade to the latest TF version as the older versions are not actively supported. \r\nKeeping extra lines in label.txt would be an issue for crashing. Please confirm the steps to reproduce the issue here. \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/61633\">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/61633\">No</a>\n" ]

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[ "Thanks for the review, Changhui! Improved the coding style according to your advice.", "Hi @changhuilin Can you please review this PR ? Thank you!", "Hi @changhuilin , what's our next step on this PR? Thank you!", "Hi @changhuilin Can you please review this PR ? Thank you!", "Hi @changhuilin Can you please review this PR ? Thank you!", "Hi @buptzyb Can you please resolve conflicts? Thank you!", "This PR is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.", "This change looks good to me.\r\n- Can you try to merge this to the head? - sorry that it takes long to get this done \r\n- Can you also expand the PR description a bit, e.g., add some experiment number to show how much improvement you observed?", " @changhuilin Thank you for taking care of this PR! Updated the description and merged to the head.", "@changhuilin So, what's our next move on this?", "@gbaned Can you help to merge? I noticed there are some check failures, and some status waiting. Which ones are real and should be addressed? Thanks!", "> @gbaned Can you help to merge? I noticed there are some check failures, and some status waiting. Which ones are real and should be addressed? Thanks!\r\n\r\nHi @changhuilin Sure thing, please click on the import/copybara details link, you can see the corresponding CL. It require runtime-team approval and presubmit checks are failing. Please take a look on it. Thank you!", "> Hi @changhuilin Sure thing, please click on the import/copybara details link, you can see the corresponding CL. It require runtime-team approval and presubmit checks are failing. Please take a look on it. Thank you!\r\n\r\nThanks, @gbaned. I got the CL - will fix the presubmit failures. I can approve on behalf of runtime-team." ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61631\">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/61631\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61630\">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/61630\">No</a>\n" ]

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[ "Hi @dmc1778 ,\r\n\r\nThe reported behaviour is replicated with Tf2.13v and tf-nightly and attached gists [2.13v](https://colab.sandbox.google.com/gist/SuryanarayanaY/87da64a1869cd267c221aa9a96a8dfcd/61629.ipynb) and [nightly](https://colab.sandbox.google.com/gist/SuryanarayanaY/b4fc16234d3d76d66b7bf15da6a7da1b/61629-nightly.ipynb) for reference.\r\n\r\nWe need to have a look into the issue whether this is intended as the error seems generated from TF C++ code itself. \r\n\r\nThanks!", "> Hi @dmc1778 ,\r\n> \r\n> The reported behaviour is replicated with Tf2.13v and tf-nightly and attached gists [2.13v](https://colab.sandbox.google.com/gist/SuryanarayanaY/87da64a1869cd267c221aa9a96a8dfcd/61629.ipynb) and [nightly](https://colab.sandbox.google.com/gist/SuryanarayanaY/b4fc16234d3d76d66b7bf15da6a7da1b/61629-nightly.ipynb) for reference.\r\n> \r\n> We need to have a look into the issue whether this is intended as the error seems generated from TF C++ code itself.\r\n> \r\n> Thanks!\r\n\r\nI think the bug is arising from the Python backend because C++ throws OP_REQUIRES failed with integer overflow. On both sides, overflow occurs. ", "This is working as intended. Those sizes are too big.", "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/61629\">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/61629\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61628\">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/61628\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61627\">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/61627\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61626\">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/61626\">No</a>\n" ]

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[ "Hi @dmc1778 , \r\n\r\nThe reported behaviour is replicated with Tf2.13v and tf-nightly and attached gists [2.13v](https://colab.sandbox.google.com/gist/SuryanarayanaY/83a3bfab80ac66fdfffa8901f0c005f7/61625.ipynb) and [nightly](https://colab.sandbox.google.com/gist/SuryanarayanaY/0452ebe256e7bdc64e3901bf83943f4a/61625-nightly.ipynb) for reference.", "@dmc1778 ,\r\n\r\nPlease refer to the responses of Developer team related to the exception raised [response1](https://github.com/tensorflow/tensorflow/issues/61630#issuecomment-1685333019) and [response2](https://github.com/tensorflow/tensorflow/issues/61629#issuecomment-1686504422) stating it as intended behaviour. \r\n\r\nThe **OP_REQUIRES_OK** tries to allocate the memory for the inputs and outputs before performing computations and it fails. The same error returned to python and its adding more details to error log.\r\n\r\nAs requested please read [SECURITY.md](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) to disclose these types of issues ", "Not an issue, it's a normal error returned to the user.", "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/61625\">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/61625\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61624\">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/61624\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61623\">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/61623\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61622\">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/61622\">No</a>\n" ]

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[ "Hi @dmc1778 , \r\n\r\nThe reported behaviour is replicated with Tf2.13v and tf-nightly and attached gists [2.13v](https://colab.sandbox.google.com/gist/SuryanarayanaY/afc553732e3db1c2c9de68833993da40/61621-2-13v.ipynb) and [nightly](https://colab.sandbox.google.com/gist/SuryanarayanaY/0d26a2f799d077b53ea3f6ac7aa4766c/61621-tf-nightly.ipynb) for reference.", "@dmc1778 ,\r\n\r\nPlease refer to the responses of Developer team related to the exception raised https://github.com/tensorflow/tensorflow/issues/61630#issuecomment-1685333019 and https://github.com/tensorflow/tensorflow/issues/61629#issuecomment-1686504422 stating it as intended behaviour.\r\n\r\nThe Op tries to allocate the memory for the inputs and outputs before performing computations and it fails. The same error returned to python and its adding more details to error log.\r\n\r\nAs requested please read [SECURITY.md](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) to disclose these types of issues.\r\n\r\nThanks!", "Not an issue, it is a normal error being returned to the user.", "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/61621\">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/61621\">No</a>\n" ]

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[ "Not an issue, that's an error that is being returned to the user instead of performing bad computations.\r\n\r\nPlease consult again the SECURITY.md guide, please don't spam with low quality issues.", "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/61620\">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/61620\">No</a>\n" ]

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[ "Hi @angerson and @mihaimaruseac thank you for the PR. It is working well, wheels are generated successfully and sanity tests are passing.", "Thank you for confirming!" ]

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[ "Hi @dmc1778 ,\r\n\r\nI think it should be OOM problem as colab crashes with` Allocation of 2149856268 exceeds 10% of free system memory.`\r\n\r\nAlso Please refer to Dev team comment on one of your earlier tickets #59359 on similar reported behaviour.\r\n\r\nRefer attached snapshot also.\r\n\r\n<img width=\"1506\" alt=\"Screenshot 2023-08-25 at 2 41 46 PM\" src=\"https://github.com/tensorflow/tensorflow/assets/116063290/73677b56-b698-472a-8283-20af61f2a6b5\">\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/61618\">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/61618\">No</a>\n" ]