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[ "@tilakrayal Hi, infos again..\r\n\r\nI've just found a log:\r\nstd::__ndk1::__tree<flatbuffers::offset<flatbuffers::string>\r\nduring mobile running.\r\n\r\nThere is also a flatbuffers file within the current app/project and I built a lib (inserted into the app/project) containing tflite libs using another flatbuffers file. Perhaps the two flatbuffers files are incompatible.\r\n\r\nIs it possible to keep the two flatbuffers files coexist?\r\n", "@picard314,\r\nCould you please provide a simple standalone code to reproduce the reported behavior and would help us to investigate further. Thank you!", "> @picard314, Could you please provide a simple standalone code to reproduce the reported behavior and would help us to investigate further. Thank you!\r\n\r\n@tilakrayal \r\nThanks for your kind attention. Since the \"two flatbuffers files\" is the cause as app can run successfully after I delete a flatbuffers file and my limited time, I shall dig it no more and please forgive me for not providing related codes for they are really a big bunch of limbs which can not be separated from each other during compiling. Thanks again.", "Hi @picard314 ,\r\n\r\nPlease let me know if you found a resolution for your issue or if you are able to provide any standalone code to reproduce this issue.", "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/66990\">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/66990\">No</a>\n" ]

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[ "Hi @stellarpower ,\r\n\r\nYou need to install GPU driver manually.After that you need to set LD_LIBRARY_PATH to the path where nvidia libraries installed. You may refer this [comment](https://github.com/tensorflow/tensorflow/issues/63362#issuecomment-1988630226) . Please refer #63362 for more details. Thanks ", "Thanks; I had done all this previously.\r\n\r\nBut I have opened as an issue irrespective of my own setup, because I believe it should be possible to get more information from the error message. Without knowing what libraries failed to be opened, just re-installing and following the instructions again isn't a particularly efficient way to debug what happened.", "Yes, I agree. I am running into the same issue now. This is particularly frustrating because of the arcane versioning of CUDA-related toolsets (i.e. the Python packages vs. CUDA vs. the dependency matrix in the documentation). For example:\r\n\r\n* TensorFlow documentation [lists](https://www.tensorflow.org/install/pip) the correct CUDA version as 11.8, so I installed that and updated my $PATH, $LD_LIBRARY_PATH, etc. accordingly (along with cudNN 8.6 as listed).\r\n* When I use a fresh Python 3.10 installation to install `tensorflow[and-cuda]` via Pip, it seems to be defaulting to CUDA runtime 12?\r\n\r\n```\r\nCollecting nvidia-cublas-cu12==12.3.4.1\r\n Using cached nvidia_cublas_cu12-12.3.4.1-py3-none-manylinux1_x86_64.whl (412.6 MB)\r\nCollecting nvidia-cuda-nvrtc-cu12==12.3.107\r\n Using cached nvidia_cuda_nvrtc_cu12-12.3.107-py3-none-manylinux1_x86_64.whl (24.9 MB)\r\nCollecting nvidia-curand-cu12==10.3.4.107\r\n Using cached nvidia_curand_cu12-10.3.4.107-py3-none-manylinux1_x86_64.whl (56.3 MB)\r\nCollecting nvidia-cusparse-cu12==12.2.0.103\r\n Using cached nvidia_cusparse_cu12-12.2.0.103-py3-none-manylinux1_x86_64.whl (197.5 MB)\r\nCollecting nvidia-nvjitlink-cu12==12.3.101\r\n Using cached nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl (20.5 MB)\r\nCollecting nvidia-nccl-cu12==2.19.3\r\n Using cached nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)\r\nCollecting nvidia-cuda-nvcc-cu12==12.3.107\r\n Using cached nvidia_cuda_nvcc_cu12-12.3.107-py3-none-manylinux1_x86_64.whl (22.0 MB)\r\nCollecting nvidia-cusolver-cu12==11.5.4.101\r\n Using cached nvidia_cusolver_cu12-11.5.4.101-py3-none-manylinux1_x86_64.whl (125.2 MB)\r\nCollecting nvidia-cudnn-cu12==8.9.7.29\r\n Using cached nvidia_cudnn_cu12-8.9.7.29-py3-none-manylinux1_x86_64.whl (704.7 MB)\r\nCollecting nvidia-cufft-cu12==11.0.12.1\r\n Using cached nvidia_cufft_cu12-11.0.12.1-py3-none-manylinux1_x86_64.whl (98.8 MB)\r\nCollecting nvidia-cuda-cupti-cu12==12.3.101\r\n Using cached nvidia_cuda_cupti_cu12-12.3.101-py3-none-manylinux1_x86_64.whl (14.0 MB)\r\nCollecting nvidia-cuda-runtime-cu12==12.3.101\r\n Using cached nvidia_cuda_runtime_cu12-12.3.101-py3-none-manylinux1_x86_64.whl (867 kB)\r\n```\r\n\r\nand relevant links in the docs only seem to link out to Docker-related stuff, like https://www.tensorflow.org/install/source so the vast majority of information on the internet is out of date.\r\n\r\nIs there any clearer guidance for how to get TensorFlow working on GPUs assuming your CUDA install is non-standard, i.e., not installed out of the Ubuntu package repo (which is infeasible in many academic settings)?\r\n\r\nThanks very much in advance.\r\n\r\nEDIT: I was able to resolve this by using the `TF_CPP_MAX_VLOG_LEVEL=3` (something buried in the above linked issue) to debug. It turned out that our new module system was nuking my `LD_LIBRARY_PATH` after cudNN was imported, so CUDA could be found but cudNN could not. Adding a note about this option to the error message around GPUs could potentially save _a lot_ of grief (even in scenarios like mine where the issue lies not with TensorFlow, but something upstream). Just a thought. May help you as well @stellarpower (seems to be what you were looking for when you opened the issue)", "@wjno thanks - I resolved the underlying problem in the end, and from memory thought I had increased the log verbosity as high as it would go, but maybe I had not. If I encounter some library problems again I'll give it a go. Cheers!\r\n", "> EDIT: I was able to resolve this by using the `TF_CPP_MAX_VLOG_LEVEL=3` (something buried in the above linked issue) to debug. It turned out that our new module system was nuking my `LD_LIBRARY_PATH` after cudNN was imported, so CUDA could be found but cudNN could not. Adding a note about this option to the error message around GPUs could potentially save _a lot_ of grief (even in scenarios like mine where the issue lies not with TensorFlow, but something upstream). Just a thought. May help you as well @stellarpower (seems to be what you were looking for when you opened the issue)\r\n\r\nHi @wjn0 , AFAIK the setting `TF_CPP_MAX_VLOG_LEVEL=3 `will only disable the debugging logs from the console.I doubt and want to know whether after disabling these logs then only cudnn libraries are being detectable? Setting right path for `LD_LIBRARY_PATH` should resolve the issue irrespective of disabling the debugging logs.Correct me if i am wrong.\r\n\r\nThanks for the info.", "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/66987\">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/66987\">No</a>\n" ]

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[ "Hi **@rsujeevan** ,\r\n- I tried to run your code on colab using TF v2.15,2.16.1 and nightly faced the same issue. Please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/f1012cd57b392cf832f5441ea5012625/66985_2-15-2-16-1-v.ipynb) here for reference. \r\n\r\nThank you!" ]

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[ "Hi @burntato ,\r\n\r\nI will replicate the issue and will get back to you.", "Hi @burntato ,\r\n\r\nCan you also share the model.tflite file please ", "> Hi @burntato ,\r\n> \r\n> Can you also share the model.tflite file please\r\n\r\nI have updated the google drive folder to contain the custom model I've used" ]

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[ "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/66978\">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/66978\">No</a>\n", "Are there any settings that i should disable in the cmake to solve this?", "Hi @Thunderzen ,\r\n\r\nLet me replicate this issue and I will get back to you.", "@sawantkumar , \r\n\r\nHi, any updates?\r\n\r\n", "Are you satisfied with the resolution of your issue?\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/66978\">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/66978\">No</a>\n", "Hi @Thunderzen ,\r\n\r\nI tried replicating your issue but kept running into errors. can you tell me which version of cmake are you using ? and since you are building for arm , i will suggest you to look up on [this](https://www.tensorflow.org/lite/guide/build_cmake_arm) .I tried cross compilaton for arm with latest tensorflow version and it worked without any issues . So, if the tflite version is not a constraint for you, can you try out with the latest tensorflow release. Meanwhile i will try to replicate your issue on my machine and will get back to you. ", "Hi @sawantkumar ,\r\n\r\nI am using CMake version 3.29. I found that different versions of tensorflow had different compatibility for a build with arm systems. For example, I found tensorflow 2.6 to be able to build on cmake and generate the libtensorflowlite.a file. So i guess it might be a version issue. If i tried even higher versions, there will be an error, usually stating that there was missing project files. So perhaps 2.6 suits best for arm system with my compiler.\r\n\r\nAnother question I would like to ask is how can i make use of libtensorflowlite.a to build projects? eg. on an ide like eclipse which requires library and include paths. It seems that I would need to build an entire project based on cmake in this minimal example shown in https://www.tensorflow.org/lite/guide/build_cmake#create_a_cmake_project_which_uses_tensorflow_lite\r\n", "Hi @Thunderzen ,\r\n\r\nCan you check [this](https://github.com/tensorflow/tflite-micro/tree/main/tensorflow/lite/micro/examples) and let me know if this is the one you are looking for.\r\n\r\n", "hi, @sawantkumar ,\r\nThe link that you recommended is not really applicable for my application as it is on microlite micro. But i think ill close the issue since tensorflow 2.6 works fine.", "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/66978\">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/66978\">No</a>\n" ]

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[ "@sushreebarsa Can you help with above query? I want to see how I can use XLA with TF to enable CUDA Graphs", "@ndeep27 There isn't a direct way to create an XLA compiled model from a TensorFlow SavedModel in TensorFlow 2. Please refer to this [official](https://www.tensorflow.org/api_docs/python/tf/xla) documentation. Could you try to consider converting your SavedModel to a TFLite model. TFLite utilizes its own interpreter and optimizations, potentially achieving similar performance benefits on mobile and embedded devices.\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/66967\">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/66967\">No</a>\n" ]

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[ "This happened to me when I tried to fit the model. I don't have any real solutions for this but if it helps, restarting the kernel has fixed it for me.", "Hi **@salmankdurrani** ,\r\n\r\n- I tried to run your code on colab using TF v2.16.1 and i am not facing any issue. Please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/7c66e11de2f4d08ba9a4a58a2aa36787/66966_2-16-1.ipynb) here for reference.\r\n- Here i imported the keras from tensorflow, It works fine for me.\r\n```\r\nimport tensorflow.keras as keras\r\n\r\n```\r\nThank you!", "This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.", "Thank you, I don't know why, but it did not work for me. I tried other ways to do it. ", "I am still facing a similar issue even with tf version 2.16.1, which version of keras should i have?", "i was facing the same issue and try to fix the issue from several website but did not find the right one and then at the end i tried chat-gpt and finally it worked for me. \r\n\r\nhere is what GPT told me :-\r\n\r\nUpdate TensorFlow and Keras: Make sure you are using compatible versions of TensorFlow and Keras. You can update these packages using pip:\r\n\r\n\r\npip install --upgrade tensorflow keras\r\n\r\n\r\nUse the correct method: If convert_to_numpy is not available, you might need to use an alternative method to convert your tensors to numpy arrays. You can use the numpy() method for TensorFlow tensors.\r\n\r\n\r\nimport tensorflow as tf\r\n\r\n# Create a TensorFlow tensor\r\ntensor = tf.constant([1, 2, 3])\r\n\r\n# Convert the tensor to a numpy array\r\nnumpy_array = tensor.numpy()\r\n\r\nprint(numpy_array) # Output: [1 2 3]\r\n\r\n", "Hi **@salmankdurrani** ,\r\n- Could you please confirm if this issue is resolved for you ? Please feel free to close the issue if it is resolved ?\r\n\r\n\r\nThank you!\r\n" ]

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[ "Couple of follow-up questions on this!!\r\n\r\nAre you using a virtual environment or conda environment? If so, have you tried installing TensorFlow 2.4 in a new environment?\r\n\r\nAlso, did you check CUDA version, GPU model and driver version compatible with TensorFlow 2.4?", "@tilakrayal,\r\nCould you please let us know specific use case that you are using tensor flow v2.5 which is pretty old and not actively supported. We always suggest using the latest tensorflow v2.15.\r\n\r\nThe tensoflow v2.4 is compatible with python - 3.6-3.8, GCC- 7.3.1, Bazel 3.1.0, cuDNN - 8.0, CUDA-11.0. Could you please try to un-install the tensorflow related softwares and try to re-install by following the official document and the tested build configurations. \r\nhttps://www.tensorflow.org/install/source#gpu\r\n\r\nThank you!", "I need Tensorflow to work on my Jetson Nano dev board that is on CUDA 10 but right now TensorFlow does not recognize my GPU as existing, so I am trying to downgrade.\r\n\r\n\r\n\r\n________________________________\r\nFrom: tilakrayal ***@***.***>\r\nSent: Monday, May 6, 2024 12:41 PM\r\nTo: tensorflow/tensorflow ***@***.***>\r\nCc: Nicholas Jan Birschbach ***@***.***>; Author ***@***.***>\r\nSubject: Re: [tensorflow/tensorflow] Unable to install old version of tensorflow (Issue #66950)\r\n\r\n\r\n@tilakrayal<https://github.com/tilakrayal>,\r\nCould you please let us know specific use case that you are using tensor flow v2.5 which is pretty old and not actively supported. We always suggest using the latest tensorflow v2.15.\r\n\r\nThe tensoflow v2.4 is compatible with python - 3.6-3.8, GCC- 7.3.1, Bazel 3.1.0, cuDNN - 8.0, CUDA-11.0. Could you please try to un-install the tensorflow related softwares and try to re-install by following the official document and the tested build configurations.\r\nhttps://www.tensorflow.org/install/source#gpu\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/66950#issuecomment-2096576082>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AXO2R6H6HDUKFD5O7VQOH3TZA66E7AVCNFSM6AAAAABHGBOPAOVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAOJWGU3TMMBYGI>.\r\nYou are receiving this because you authored the thread.Message ID: ***@***.***>\r\n", "@Nicholas-B1,\r\nAs mentioned the tensoflow v2.4 is compatible with python - 3.6-3.8, GCC- 7.3.1, Bazel 3.1.0, cuDNN - 8.0, CUDA-11.0. The GPU might not detect and face different warnings if the compatible versions are unmatched with the respective TensorFlow version. 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/66950\">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/66950\">No</a>\n" ]

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[ "@penpornk Just a heads-up that https://github.com/tensorflow/tensorflow/pull/58204 PR got reverted due to ARM unit test failures. I have pushed a fix in this PR.", "Hi @mdfaijul Can you please rebase your branch and resolve the conflicts? Thank you!\r\n\r\n", "@gbaned @penpornk I have resolved all the merge conflicts. Can you please review this PR? Thanks.", "Hi @penpornk Can you please review this PR? Thank you!" ]