TFOD API 安装时出现 Protobuf 错误：ImportError：无法导入名称“builder”

问题描述 投票：0回答：2

我正在尝试按照本教程安装 Tensorflow 对象检测 API。当我到达最后时，在尝试 

python object_detection/builders/model_builder_tf2_test.py
命令时，出现以下错误：

Traceback (most recent call last):
  File "object_detection/builders/model_builder_tf2_test.py", line 25, in <module>
    from object_detection.builders import model_builder
  File "/home/deeplearning/model_compression/TFOD-TRT/venv/lib/python3.6/site-packages/object_detection/builders/model_builder.py", line 23, in <module>
    from object_detection.builders import anchor_generator_builder
  File "/home/deeplearning/model_compression/TFOD-TRT/venv/lib/python3.6/site-packages/object_detection/builders/anchor_generator_builder.py", line 27, in <module>
    from object_detection.protos import anchor_generator_pb2
  File "/home/deeplearning/model_compression/TFOD-TRT/venv/lib/python3.6/site-packages/object_detection/protos/anchor_generator_pb2.py", line 5, in <module>
    from google.protobuf.internal import builder as _builder
ImportError: cannot import name 'builder'

这些是我的系统设置：

  • 操作系统：Ubuntu 18.04
  • Python：3.6
  • 协议：3.12.3
  • 张量流：2.6.2
  • CUDA：11.6
  • cudNN：8.3.2
  • 张量RT：8.4.0

您可以在这里查看：

$ nvidia-smi
Fri Mar 18 15:35:30 2022       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.47.03    Driver Version: 510.47.03    CUDA Version: 11.6     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  On   | 00000000:01:00.0 Off |                  N/A |
| N/A   48C    P0    N/A /  N/A |    412MiB /  4096MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1144      G   /usr/lib/xorg/Xorg                 28MiB |
|    0   N/A  N/A      1371      G   /usr/bin/gnome-shell               67MiB |
|    0   N/A  N/A      1622      G   /usr/lib/xorg/Xorg                135MiB |
|    0   N/A  N/A      1798      G   /usr/bin/gnome-shell               24MiB |
|    0   N/A  N/A      2163      G   /usr/lib/firefox/firefox          149MiB |
|    0   N/A  N/A      6459      G   /usr/lib/firefox/firefox            1MiB |
+-----------------------------------------------------------------------------+


$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Thu_Feb_10_18:23:41_PST_2022
Cuda compilation tools, release 11.6, V11.6.112
Build cuda_11.6.r11.6/compiler.30978841_0


$ /sbin/ldconfig -N -v $(sed 's/:/ /' <<< $LD_LIBRARY_PATH) 2>/dev/null | grep libcudnn
    libcudnn_cnn_train.so.8 -> libcudnn_cnn_train.so.8.3.2
    libcudnn_adv_train.so.8 -> libcudnn_adv_train.so.8.3.2
    libcudnn_adv_infer.so.8 -> libcudnn_adv_infer.so.8.3.2
    libcudnn_ops_infer.so.8 -> libcudnn_ops_infer.so.8.3.2
    libcudnn_ops_train.so.8 -> libcudnn_ops_train.so.8.3.2
    libcudnn.so.8 -> libcudnn.so.8.3.2
    libcudnn_cnn_infer.so.8 -> libcudnn_cnn_infer.so.8.3.2

(venv) deeplearning@deeplearning:~/model_compression/models/research$ dpkg -l | grep TensorRT
ii  graphsurgeon-tf                                             8.4.0-1+cuda11.6                                amd64        GraphSurgeon for TensorRT package
ii  libnvinfer-bin                                              8.4.0-1+cuda11.6                                amd64        TensorRT binaries
ii  libnvinfer-dev                                              8.4.0-1+cuda11.6                                amd64        TensorRT development libraries and headers
ii  libnvinfer-doc                                              8.4.0-1+cuda11.6                                all          TensorRT documentation
ii  libnvinfer-plugin-dev                                       8.4.0-1+cuda11.6                                amd64        TensorRT plugin libraries
ii  libnvinfer-plugin8                                          8.4.0-1+cuda11.6                                amd64        TensorRT plugin libraries
ii  libnvinfer-samples                                          8.4.0-1+cuda11.6                                all          TensorRT samples
ii  libnvinfer8                                                 8.4.0-1+cuda11.6                                amd64        TensorRT runtime libraries
ii  libnvonnxparsers-dev                                        8.4.0-1+cuda11.6                                amd64        TensorRT ONNX libraries
ii  libnvonnxparsers8                                           8.4.0-1+cuda11.6                                amd64        TensorRT ONNX libraries
ii  libnvparsers-dev                                            8.4.0-1+cuda11.6                                amd64        TensorRT parsers libraries
ii  libnvparsers8                                               8.4.0-1+cuda11.6                                amd64        TensorRT parsers libraries
ii  onnx-graphsurgeon                                           8.4.0-1+cuda11.6                                amd64        ONNX GraphSurgeon for TensorRT package
ii  python3-libnvinfer                                          8.4.0-1+cuda11.6                                amd64        Python 3 bindings for TensorRT
ii  python3-libnvinfer-dev                                      8.4.0-1+cuda11.6                                amd64        Python 3 development package for TensorRT
ii  tensorrt                                                    8.4.0.6-1+cuda11.6                              amd64        Meta package of TensorRT
ii  uff-converter-tf                                            8.4.0-1+cuda11.6                                amd64        UFF converter for TensorRT package


$ protoc --version
libprotoc 3.12.3


pip list
Package                       Version
----------------------------- ---------
absl-py                       0.12.0
apache-beam                   2.37.0
appdirs                       1.4.4
astunparse                    1.6.3
attrs                         21.4.0
avro-python3                  1.10.2
beautifulsoup4                4.10.0
cached-property               1.5.2
cachetools                    4.2.4
certifi                       2021.10.8
charset-normalizer            2.0.12
clang                         5.0
cloudpickle                   2.0.0
colorama                      0.4.4
contextlib2                   21.6.0
crcmod                        1.7
cycler                        0.11.0
Cython                        0.29.28
dataclasses                   0.8
decorator                     5.1.1
dill                          0.3.1.1
dm-tree                       0.1.6
docopt                        0.6.2
fastavro                      1.4.7
flatbuffers                   1.12
gast                          0.4.0
gin-config                    0.5.0
google                        3.0.0
google-api-core               2.7.1
google-api-python-client      2.41.0
google-auth                   1.35.0
google-auth-httplib2          0.1.0
google-auth-oauthlib          0.4.6
google-cloud                  0.34.0
google-pasta                  0.2.0
googleapis-common-protos      1.56.0
grpcio                        1.44.0
h5py                          3.1.0
hdfs                          2.6.0
httplib2                      0.19.1
idna                          3.3
importlib-metadata            4.8.3
importlib-resources           5.4.0
joblib                        1.1.0
kaggle                        1.5.12
keras                         2.6.0
Keras-Preprocessing           1.1.2
kiwisolver                    1.3.1
lvis                          0.5.3
lxml                          4.8.0
Mako                          1.1.6
Markdown                      3.3.6
MarkupSafe                    2.0.1
matplotlib                    3.3.4
neural-structured-learning    1.3.1
numpy                         1.19.5
oauth2client                  4.1.3
oauthlib                      3.2.0
object-detection              0.1
onnx                          1.8.1
onnxruntime                   1.8.0
opencv-python                 4.5.5.64
opencv-python-headless        4.5.5.64
opt-einsum                    3.3.0
orjson                        3.6.1
pandas                        1.1.5
Pillow                        8.2.0
pip                           21.3.1
pkg_resources                 0.0.0
platformdirs                  2.4.0
portalocker                   2.4.0
promise                       2.3
proto-plus                    1.20.3
protobuf                      3.19.4
psutil                        5.9.0
py-cpuinfo                    8.0.0
pyarrow                       6.0.1
pyasn1                        0.4.8
pyasn1-modules                0.2.8
pycocotools                   2.0
pycuda                        2021.1
pydot                         1.4.2
pymongo                       3.12.3
pyparsing                     2.4.7
python-dateutil               2.8.2
python-slugify                6.1.1
pytools                       2022.1.2
pytz                          2021.3
PyYAML                        6.0
regex                         2022.3.15
requests                      2.27.1
requests-oauthlib             1.3.1
rsa                           4.8
sacrebleu                     2.0.0
scikit-learn                  0.24.2
scipy                         1.5.4
sentencepiece                 0.1.96
seqeval                       1.2.2
setuptools                    59.6.0
six                           1.15.0
soupsieve                     2.3.1
tabulate                      0.8.9
tensorboard                   2.6.0
tensorboard-data-server       0.6.1
tensorboard-plugin-wit        1.8.1
tensorflow                    2.6.2
tensorflow-addons             0.14.0
tensorflow-datasets           4.5.2
tensorflow-estimator          2.6.0
tensorflow-hub                0.12.0
tensorflow-io                 0.21.0
tensorflow-io-gcs-filesystem  0.21.0
tensorflow-metadata           1.2.0
tensorflow-model-optimization 0.7.1
tensorflow-text               2.6.0
termcolor                     1.1.0
text-unidecode                1.3
tf-models-official            2.7.1
tf-slim                       1.1.0
tf2onnx                       1.8.1
threadpoolctl                 3.1.0
tqdm                          4.63.0
typeguard                     2.13.3
typing-extensions             3.7.4.3
uritemplate                   4.1.1
urllib3                       1.26.9
Werkzeug                      2.0.3
wheel                         0.37.1
wrapt                         1.12.1
zipp                          3.6.0

缺少什么？我尝试重新安装所有内容，从源代码安装 protobuf 等等。 Tensorflow 可以工作，但这个不行。

感谢您的宝贵时间， 弗兰.

编辑1

一些可能很重要的信息。

我尝试过切换python版本并重新安装所有NVIDIA/CUDA环境。好像跟这个没什么关系

名为 builder 的包应该在这里：

~/model_compression/TFOD-TRT/venv/lib/python3.8/site-packages/google/protobuf/internal$ ls
_api_implementation.cpython-38-x86_64-linux-gnu.so  __init__.py
api_implementation.py                               message_listener.py
containers.py                                       __pycache__
decoder.py                                          python_message.py
encoder.py                                          type_checkers.py
enum_type_wrapper.py                                well_known_types.py
extension_dict.py                                   wire_format.py

但事实并非如此。功能解析器不应该自己做这件事吗？

编辑2

为tensorflow-model-garden添加标签

tensorflow installation ubuntu-18.04 protoc tensorflow-model-garden
2个回答
0
投票

收到相同的错误消息。

幸运的是，经过几次尝试后解决了，但我无法准确指出。 希望您能解决问题。

尝试 

conda install protobuf==3.14
并检查 conda 依赖项是否具有 libprotobuf 并且 pip 依赖项是否具有 protobuf。

以下是我的案例（环境）；

# environment.yaml

name: tfod
channels:
  - defaults
dependencies:
  - ca-certificates=2022.07.19=haa95532_0
  - certifi=2022.6.15=py39haa95532_0
  - libprotobuf=3.14.0=h23ce68f_0 ##### this one and (below↓)#####
  - openssl=1.1.1q=h2bbff1b_0
  - pip=22.1.2=py39haa95532_0
  - python=3.9.12=h6244533_0
  - setuptools=61.2.0=py39haa95532_0
  - six=1.16.0=pyhd3eb1b0_1
  - sqlite=3.39.2=h2bbff1b_0
  - tzdata=2022a=hda174b7_0
  - vc=14.2=h21ff451_1
  - vs2015_runtime=14.27.29016=h5e58377_2
  - wheel=0.37.1=pyhd3eb1b0_0
  - wincertstore=0.2=py39haa95532_2
  - zlib=1.2.12=h8cc25b3_2
  - pip:
    - apache-beam==2.40.0
    - astunparse==1.6.3
    - avro-python3==1.10.2
    - cloudpickle==2.1.0
    - contextlib2==21.6.0
    - crcmod==1.7
    - dill==0.3.1.1
    - docopt==0.6.2
    - fastavro==1.5.4
    - flatbuffers==1.12
    - gast==0.4.0
    - google-auth-oauthlib==0.4.6
    - google-pasta==0.2.0
    - grpcio==1.47.0
    - h5py==3.7.0
    - hdfs==2.7.0
    - importlib-metadata==4.12.0
    - keras==2.9.0
    - keras-preprocessing==1.1.2
    - libclang==14.0.6
    - lvis==0.5.3
    - markdown==3.4.1
    - markupsafe==2.1.1
    - numpy==1.22.4
    - oauthlib==3.2.0
    - object-detection==0.1
    - opencv-python==4.6.0.66
    - opt-einsum==3.3.0
    - orjson==3.7.11
    - proto-plus==1.22.0
    - protobuf==3.19.4 ##### this one #####
    - pyarrow==7.0.0
    - pydot==1.4.2
    - pymongo==3.12.3
    - pyparsing==2.4.7
    - requests-oauthlib==1.3.1
    - tensorboard==2.9.1
    - tensorboard-data-server==0.6.1
    - tensorboard-plugin-wit==1.8.1
    - tensorflow==2.9.1
    - tensorflow-estimator==2.9.0
    - tensorflow-io==0.26.0
    - tensorflow-io-gcs-filesystem==0.26.0
    - tensorflow-text==2.9.0
    - tf-models-official==2.9.2
    - werkzeug==2.2.2
    - wrapt==1.14.1
prefix: C:\Users\user\anaconda3\envs\tfod
0
投票

我收到了同样的错误消息

已解决

请按照以下步骤操作：

  1. 下载最新版本的procobuf
    pip install --upgrade proctobuf
    现在您将收到另一个类似于以下内容的错误： 这是因为https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/install.html给出的步骤安装了旧版本的tensorflow，只能与3.20以下的proctobuf一起使用.
  2. 我假设您也使用 anaconda 环境。使用 
    conda info --envs
    3. 检查保存环境的路径
  3. 在您的环境文件中，将 builder.py 从 
    .../Lib/site-packages/google/protobuf/internal
    临时复制到计算机上的任何其他文件夹。
  4. 将proctobuf版本降级到与tensorflow兼容的较低版本。对我来说它低于 3.20，它后面的最后一个版本是3.19.6。
  5. 最后将builder.py文件复制回
    .../Lib/site-packages/google/protobuf/internal
    文件夹中。
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