Colab：(0) 未实现：未找到 DNN 库

Question

我在 Google Colab 中预训练了目标检测模型（Google Colab + TensorFlow），每周对我拥有的新图像运行两三次，从去年到本周一切都很好。现在，当我尝试运行模型时，我收到以下消息：

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Graph execution error:\n\n2 root error(s) found.\n  (0) UNIMPLEMENTED:  DNN library is not found.\n     [[{{node functional_1/conv1_conv/Conv2D}}]]\n     [[StatefulPartitionedCall/SecondStagePostprocessor/BatchMultiClassNonMaxSuppression/MultiClassNonMaxSuppression/Reshape_5/_126]]\n  (1) UNIMPLEMENTED:  DNN library is not found.\n     [[{{node functional_1/conv1_conv/Conv2D}}]]\n0 successful operations.\n0 derived errors ignored. [Op:__inference_restored_function_body_27380] ***\n

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以前从未发生过。

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在运行模型之前，我必须使用以下命令安装 Tensor Flow 对象检测 API：

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Graph execution error:\n\n2 root error(s) found.\n  (0) UNIMPLEMENTED:  DNN library is not found.\n     [[{{node functional_1/conv1_conv/Conv2D}}]]\n     [[StatefulPartitionedCall/SecondStagePostprocessor/BatchMultiClassNonMaxSuppression/MultiClassNonMaxSuppression/Reshape_5/_126]]\n  (1) UNIMPLEMENTED:  DNN library is not found.\n     [[{{node functional_1/conv1_conv/Conv2D}}]]\n0 successful operations.\n0 derived errors ignored. [Op:__inference_restored_function_body_27380] ***\n

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这是命令的输出：

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Processing /content/gdrive/MyDrive/models/research\n  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\nCollecting avro-python3\n  Downloading avro-python3-1.10.2.tar.gz (38 kB)\nCollecting apache-beam\n  Downloading apache_beam-2.35.0-cp37-cp37m-manylinux2010_x86_64.whl (9.9 MB)\n     |\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88\xe2\x96\x88| 9.9 MB 1.6 MB/s\nRequirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from object-detection==0.1) (7.1.2)\nRequirement already satisfied: lxml in /usr/local/lib/python3.7/dist-packages (from object-detection==0.1) (4.2.6)\nRequirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from 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Answer 1

这对我有用（Colab）

# Check libcudnn8 version
!apt-cache policy libcudnn8

# Install latest version
!apt install --allow-change-held-packages libcudnn8=8.4.1.50-1+cuda11.6

# Export env variables
!export PATH=/usr/local/cuda-11.4/bin${PATH:+:${PATH}}
!export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
!export LD_LIBRARY_PATH=/usr/local/cuda-11.4/include:$LD_LIBRARY_PATH
!export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/extras/CUPTI/lib64

# Install tensorflow
!pip install tflite-model-maker==0.4.0
!pip uninstall -y tensorflow && pip install -q tensorflow==2.9.1
!pip install pycocotools==2.0.4
!pip install opencv-python-headless==4.6.0.66

Answer 2

如果您从 Github 克隆 Tensorflow Repo，请将 ..\models\research\object_detection\packages\tf2 中的 setup.py 更改为

'tensorflow==2.7.0',
'tf-models-official==2.7.0',
'tensorflow_io==0.23.1',

因此，当您安装 TFOD 时，它将安装 Tensorflow 2.7 而不是 2.8。但请确保在从 github 克隆存储库后进行更改。否则你的更改将会消失

Answer 3

这看起来像是 Tensorflow、cuda 和模型存储库代码的兼容性问题。

尝试在 colab 开始时安装以下 TensorFlow 版本和 cuda 版本。应该可以工作。

!pip install tensorflow==2.8
!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

Answer 4

对于有同样错误的人：安装 object_detection 后只需运行以下命令重新安装tensorflow=2.7.0：

!pip install tensorflow==2.7.0

之后您需要重新启动运行时（菜单 -> 运行时 -> 重新启动运行时）

这将解决“(0)未实现：未找到DNN库”问题