ImportError: /usr/lib/x86_64-linux-gnu/libcuda.so.1: file too short

[JS00000]

I use Docker to run this project, but meet some problems.

The progress is below:

docker image build -t ppdemo . docker run --name my_mongo -p 27017:27017 -d mongo docker run -t --link my_mongo:mongo -v $PWD:/app/Personae ppdemo spider/stock_spider.py

It is fine now. But some errors happened when python import tensorflow.

$ docker run -t --link my_mongo:mongo -v $PWD:/app/Personae ppdemo algorithm/SL/DualAttnRNN.py
Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "/usr/lib/python3.5/imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: /usr/lib/x86_64-linux-gnu/libcuda.so.1: file too short

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "algorithm/SL/DualAttnRNN.py", line 3, in <module>
    import tensorflow as tf
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/__init__.py", line 49, in <module>
    from tensorflow.python import pywrap_tensorflow
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 72, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "/usr/lib/python3.5/imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: /usr/lib/x86_64-linux-gnu/libcuda.so.1: file too short

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/install_sources#common_installation_problems

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

I am a noob in using docker. May you tell me what's wrong with the progress?

[Ceruleanacg]

It seems like your CUDA version or cuDNN version is not correct, can you tell me what version are they?

[JS00000]

I did nothing with CUDA or cuDNN in Docker. Just build the docker image using this project's Dockerfile.

Outside the Docker, I installed CUDA8.0 && CUDA9.1 in macOS, and CUDA9.1 is linked.

$ ls /Developer/NVIDIA
CUDA-8.0 CUDA-9.1

$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Tue_Dec_19_21:36:29_CST_2017
Cuda compilation tools, release 9.1, V9.1.128

And my cuDNN's version seems like is 5, but it is not work with CUDA9.1 now.

$ ls /usr/local/cuda/lib | grep cudnn
libcudnn.5.dylib
libcudnn.dylib
libcudnn_static.a

$ cat /usr/local/cuda/include/cudnn.h
cat: /usr/local/cuda/include/cudnn.h: No such file or directory

Should I install the right version of CUDA and cuDNN outside the Docker? Or install the CUDA8.0 and cuDNN6 in Docker manually? Thank you very much for explaining my confusion.

[Ceruleanacg]

• macOS
  1. If the GPU of your mac is provided by NVIDIA, then you can use CUDA, and the version should be CUDA8, cuDNN6. Then you could run this project by the docker image mentioned in README.
  2. If the GPU of your mac is not provided by NVDIA, then you cannot use CUDA and tensorflow-gpu and the Docker image of this project, I did not mention it in README, sorry for that, for this case, you could only use tensorflow-cpu and conda to build the environment and run this project.

It's recommended to use docker on Ubuntu with NVIDIA GPU.

[wangzhangup]

@JS00000 You should use Nvidia-docker2.

[Yangget]

nvidia-docker run -dit -p 8888:8888 -p 6006:6006 tensorflow/newbuild:2.0 /bin/bash like me .you should use nvidia-docker to run