Colab：（0）未实现：未找到 DNN 库
Colab: (0) UNIMPLEMENTED: DNN library is not found
我在 Google Colab 中预训练了对象检测模型 (Google Colab + TensorFlow)，我 运行 每周对我拥有的新图像和所有内容进行 2-3 次训练去年到本周都很好。现在，当我尝试 运行 模型时，我收到以下消息：
Graph execution error:
2 root error(s) found.
(0) UNIMPLEMENTED: DNN library is not found.
[[{{node functional_1/conv1_conv/Conv2D}}]]
[[StatefulPartitionedCall/SecondStagePostprocessor/BatchMultiClassNonMaxSuppression/MultiClassNonMaxSuppression/Reshape_5/_126]]
(1) UNIMPLEMENTED: DNN library is not found.
[[{{node functional_1/conv1_conv/Conv2D}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_restored_function_body_27380] ***
以前从未发生过。
在我可以 运行 我的模型之前，我必须使用以下命令安装 Tensor Flow 对象检测 API：
import os
os.chdir('/project/models/research')
!protoc object_detection/protos/*.proto --python_out=.
!cp object_detection/packages/tf2/setup.py .
!python -m pip install .
这是命令的输出：
Processing /content/gdrive/MyDrive/models/research
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.
pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.
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Building wheels for collected packages: object-detection, py-cpuinfo, dill, avro-python3, seqeval
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Installing collected packages: requests, protobuf, numpy, tf-estimator-nightly, tensorflow-io-gcs-filesystem, tensorboard, keras, tensorflow, portalocker, dill, colorama, tf-slim, tensorflow-text, tensorflow-model-optimization, tensorflow-addons, seqeval, sentencepiece, sacrebleu, pyyaml, pymongo, py-cpuinfo, proto-plus, orjson, opencv-python-headless, hdfs, fastavro, tf-models-official, tensorflow-io, lvis, avro-python3, apache-beam, object-detection
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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
yellowbrick 1.3.post1 requires numpy<1.20,>=1.16.0, but you have numpy 1.20.3 which is incompatible.
multiprocess 0.70.12.2 requires dill>=0.3.4, but you have dill 0.3.1.1 which is incompatible.
google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.
datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.
albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.
Successfully installed apache-beam-2.35.0 avro-python3-1.10.2 colorama-0.4.4 dill-0.3.1.1 fastavro-1.4.9 hdfs-2.6.0 keras-2.8.0 lvis-0.5.3 numpy-1.20.3 object-detection-0.1 opencv-python-headless-4.5.5.62 orjson-3.6.6 portalocker-2.3.2 proto-plus-1.19.9 protobuf-3.19.4 py-cpuinfo-8.0.0 pymongo-3.12.3 pyyaml-5.4.1 requests-2.27.1 sacrebleu-2.0.0 sentencepiece-0.1.96 seqeval-1.2.2 tensorboard-2.8.0 tensorflow-2.8.0 tensorflow-addons-0.15.0 tensorflow-io-0.24.0 tensorflow-io-gcs-filesystem-0.24.0 tensorflow-model-optimization-0.7.0 tensorflow-text-2.8.1 tf-estimator-nightly-2.8.0.dev2021122109 tf-models-official-2.8.0 tf-slim-1.1.0
我注意到此命令卸载 tensorflow 2.7 并安装 tensorflow 2.8。我不确定它以前发生过。也许这就是 DNN 库 link 缺少某些东西的原因？
我可以确认这些：
- 预训练模型或已安装的模型或 object_detection 我一年前下载的源文件没有任何变化。
- 我尝试 运行 命令 !pip install dnn - 不工作
- 我尝试重新启动 运行time（没有断开连接）- 不工作
有人可以帮忙吗？谢谢
上周五我也遇到了同样的情况。我认为这与 Google Colab 中的 Cuda 安装有关，但我不知道确切原因
对于有同样错误的人：安装后 object_detection 只需要通过 运行 这个命令再次重新安装 tensorflow=2.7.0：
!pip install tensorflow==2.7.0
您需要在此之后重新启动运行时（菜单 -> 运行时 -> 重新启动运行时）
这将解决“(0) UNIMPLEMENTED: DNN library is not found”问题
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。但是请确保在从 github 克隆存储库后进行更改。否则您的更改将会消失
我在 Google Colab 中预训练了对象检测模型 (Google Colab + TensorFlow)，我 运行 每周对我拥有的新图像和所有内容进行 2-3 次训练去年到本周都很好。现在，当我尝试 运行 模型时，我收到以下消息：
Graph execution error:
2 root error(s) found.
(0) UNIMPLEMENTED: DNN library is not found.
[[{{node functional_1/conv1_conv/Conv2D}}]]
[[StatefulPartitionedCall/SecondStagePostprocessor/BatchMultiClassNonMaxSuppression/MultiClassNonMaxSuppression/Reshape_5/_126]]
(1) UNIMPLEMENTED: DNN library is not found.
[[{{node functional_1/conv1_conv/Conv2D}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_restored_function_body_27380] ***
以前从未发生过。
在我可以 运行 我的模型之前，我必须使用以下命令安装 Tensor Flow 对象检测 API：
import os
os.chdir('/project/models/research')
!protoc object_detection/protos/*.proto --python_out=.
!cp object_detection/packages/tf2/setup.py .
!python -m pip install .
这是命令的输出：
Processing /content/gdrive/MyDrive/models/research
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.
pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.
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Building wheels for collected packages: object-detection, py-cpuinfo, dill, avro-python3, seqeval
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Installing collected packages: requests, protobuf, numpy, tf-estimator-nightly, tensorflow-io-gcs-filesystem, tensorboard, keras, tensorflow, portalocker, dill, colorama, tf-slim, tensorflow-text, tensorflow-model-optimization, tensorflow-addons, seqeval, sentencepiece, sacrebleu, pyyaml, pymongo, py-cpuinfo, proto-plus, orjson, opencv-python-headless, hdfs, fastavro, tf-models-official, tensorflow-io, lvis, avro-python3, apache-beam, object-detection
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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
yellowbrick 1.3.post1 requires numpy<1.20,>=1.16.0, but you have numpy 1.20.3 which is incompatible.
multiprocess 0.70.12.2 requires dill>=0.3.4, but you have dill 0.3.1.1 which is incompatible.
google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.
datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.
albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.
Successfully installed apache-beam-2.35.0 avro-python3-1.10.2 colorama-0.4.4 dill-0.3.1.1 fastavro-1.4.9 hdfs-2.6.0 keras-2.8.0 lvis-0.5.3 numpy-1.20.3 object-detection-0.1 opencv-python-headless-4.5.5.62 orjson-3.6.6 portalocker-2.3.2 proto-plus-1.19.9 protobuf-3.19.4 py-cpuinfo-8.0.0 pymongo-3.12.3 pyyaml-5.4.1 requests-2.27.1 sacrebleu-2.0.0 sentencepiece-0.1.96 seqeval-1.2.2 tensorboard-2.8.0 tensorflow-2.8.0 tensorflow-addons-0.15.0 tensorflow-io-0.24.0 tensorflow-io-gcs-filesystem-0.24.0 tensorflow-model-optimization-0.7.0 tensorflow-text-2.8.1 tf-estimator-nightly-2.8.0.dev2021122109 tf-models-official-2.8.0 tf-slim-1.1.0
我注意到此命令卸载 tensorflow 2.7 并安装 tensorflow 2.8。我不确定它以前发生过。也许这就是 DNN 库 link 缺少某些东西的原因？
我可以确认这些：
- 预训练模型或已安装的模型或 object_detection 我一年前下载的源文件没有任何变化。
- 我尝试 运行 命令 !pip install dnn - 不工作
- 我尝试重新启动 运行time（没有断开连接）- 不工作
有人可以帮忙吗？谢谢
上周五我也遇到了同样的情况。我认为这与 Google Colab 中的 Cuda 安装有关，但我不知道确切原因
对于有同样错误的人：安装后 object_detection 只需要通过 运行 这个命令再次重新安装 tensorflow=2.7.0：
!pip install tensorflow==2.7.0
您需要在此之后重新启动运行时（菜单 -> 运行时 -> 重新启动运行时）
这将解决“(0) UNIMPLEMENTED: DNN library is not found”问题
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。但是请确保在从 github 克隆存储库后进行更改。否则您的更改将会消失