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ImportError：libcublas.so.10.0：共有オブジェクトファイルを開けません：そのようなファイルまたはディレクタはありません

Ubuntu 18.04にCuda 10.1とcudnnをインストールしましたが、nvccとnvidia-smiと入力すると正しくインストールされているようです。適切な応答が得られます。

    user:~$ nvcc -V
    nvcc: NVIDIA (R) Cuda compiler driver
    Copyright (c) 2005-2019 NVIDIA Corporation
    Built on Fri_Feb__8_19:08:17_PST_2019
    Cuda compilation tools, release 10.1, V10.1.105
    user:~$ nvidia-smi 
    Mon Mar 18 14:36:47 2019       
    +-----------------------------------------------------------------------------+
    | NVIDIA-SMI 418.43       Driver Version: 418.43       CUDA Version: 10.1     |
    |-------------------------------+----------------------+----------------------+
    | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
    | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
    |===============================+======================+======================|
    |   0  Quadro K5200        Off  | 00000000:03:00.0  On |                  Off |
    | 26%   39C    P8    14W / 150W |    225MiB /  8118MiB |      0%      Default |
    +-------------------------------+----------------------+----------------------+

    +-----------------------------------------------------------------------------+
    | Processes:                                                       GPU Memory |
    |  GPU       PID   Type   Process name                             Usage      |
    |=============================================================================|
    |    0      1538      G   /usr/lib/xorg/Xorg                            32MiB |
    |    0      1583      G   /usr/bin/gnome-Shell                           5MiB |
    |    0      3008      G   /usr/lib/xorg/Xorg                           100MiB |
    |    0      3120      G   /usr/bin/gnome-Shell                          82MiB |
    +-----------------------------------------------------------------------------+

以下を使用してtensorflowをインストールしました：user:~$ Sudo pip3 install --upgrade tensorflow-gpu

The directory '/home/amin/.cache/pip/http' or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with Sudo, you may want Sudo's -H flag.
The directory '/home/amin/.cache/pip' or its parent directory is not owned by the current user and caching wheels has been disabled. check the permissions and owner of that directory. If executing pip with Sudo, you may want Sudo's -H flag.
Requirement already up-to-date: tensorflow-gpu in /usr/local/lib/python3.6/dist-packages (1.13.1)
Requirement already satisfied, skipping upgrade: keras-applications>=1.0.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (1.0.7)
Requirement already satisfied, skipping upgrade: protobuf>=3.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (3.6.1)
Requirement already satisfied, skipping upgrade: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (0.32.3)
Requirement already satisfied, skipping upgrade: absl-py>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (0.7.0)
Requirement already satisfied, skipping upgrade: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (1.0.9)
Requirement already satisfied, skipping upgrade: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (0.2.2)
Requirement already satisfied, skipping upgrade: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (1.1.0)
Requirement already satisfied, skipping upgrade: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (1.18.0)
Requirement already satisfied, skipping upgrade: tensorflow-estimator<1.14.0rc0,>=1.13.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (1.13.0)
Requirement already satisfied, skipping upgrade: six>=1.10.0 in /usr/lib/python3/dist-packages (from tensorflow-gpu) (1.11.0)
Requirement already satisfied, skipping upgrade: numpy>=1.13.3 in /usr/lib/python3/dist-packages (from tensorflow-gpu) (1.13.3)
Requirement already satisfied, skipping upgrade: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (0.7.1)
Requirement already satisfied, skipping upgrade: tensorboard<1.14.0,>=1.13.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu) (1.13.1)
Requirement already satisfied, skipping upgrade: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.6->tensorflow-gpu) (2.9.0)
Requirement already satisfied, skipping upgrade: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.1->tensorflow-gpu) (40.6.3)
Requirement already satisfied, skipping upgrade: mock>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-estimator<1.14.0rc0,>=1.13.0->tensorflow-gpu) (2.0.0)
Requirement already satisfied, skipping upgrade: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow-gpu) (0.14.1)
Requirement already satisfied, skipping upgrade: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow-gpu) (3.0.1)
Requirement already satisfied, skipping upgrade: pbr>=0.11 in /usr/local/lib/python3.6/dist-packages (from mock>=2.0.0->tensorflow-estimator<1.14.0rc0,>=1.13.0->tensorflow-gpu) (5.1.1)

しかし、テンソルフローをインポートしようとすると、libcublas.so.10.0に関するエラーが発生します。

    user:~$ python3
    Python 3.6.7 (default, Oct 22 2018, 11:32:17) 
    [GCC 8.2.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import tensorflow as tf
    Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
        from tensorflow.python.pywrap_tensorflow_internal import *
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
        _pywrap_tensorflow_internal = swig_import_helper()
      File "/usr/local/lib/python3.6/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/python3.6/imp.py", line 243, in load_module
        return load_dynamic(name, filename, file)
      File "/usr/lib/python3.6/imp.py", line 343, in load_dynamic
        return _load(spec)
    ImportError: libcublas.so.10.0: cannot open shared object file: No such file or directory

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/__init__.py", line 24, in <module>
        from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/__init__.py", line 49, in <module>
        from tensorflow.python import pywrap_tensorflow
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in <module>
        raise ImportError(msg)
    ImportError: Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
        from tensorflow.python.pywrap_tensorflow_internal import *
      File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
        _pywrap_tensorflow_internal = swig_import_helper()
      File "/usr/local/lib/python3.6/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/python3.6/imp.py", line 243, in load_module
        return load_dynamic(name, filename, file)
      File "/usr/lib/python3.6/imp.py", line 343, in load_dynamic
        return _load(spec)
    ImportError: libcublas.so.10.0: cannot open shared object file: No such file or directory


    Failed to load the native TensorFlow runtime.

    See https://www.tensorflow.org/install/errors

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

何が欠けていますか？どうすれば解決できますか？

ありがとう

tensorflowcudaubuntu-18.04
13
Amin Merati

にいる、

Tensorflowモデルパッケージからimagenetチュートリアルを実行しようとすると、同じエラーが発生します https://github.com/tensorflow/models/tree/master/tutorials/image/imagenet

 python3 classify_image.py
 ...
 2019-07-21 22:29:58.367858: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcudart.so.10.0'; dlerror: libcudart.so.10.0: cannot open shared object file: No such file or directory
 2019-07-21 22:29:58.367982: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory
 2019-07-21 22:29:58.368112: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcufft.so.10.0'; dlerror: libcufft.so.10.0: cannot open shared object file: No such file or directory
 2019-07-21 22:29:58.368234: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcurand.so.10.0'; dlerror: libcurand.so.10.0: cannot open shared object file: No such file or directory
 2019-07-21 22:29:58.368369: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcusolver.so.10.0'; dlerror: libcusolver.so.10.0: cannot open shared object file: No such file or directory
 2019-07-21 22:29:58.368498: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcusparse.so.10.0'; dlerror: libcusparse.so.10.0: cannot open shared object file: No such file or directory
 2019-07-21 22:29:58.374333: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7

どこかにバージョンの非互換性があり、おそらくテンソルフローがあると思いますが、それでもcudaライブラリによって提供されるバイナリの古いバージョンに依存しています。バイナリが保存されている場所に移動し、10.0という名前で10.1またはライブラリのデフォルトバージョンをターゲットとするリンクを作成すると、問題が解決するようです。

 # cd /usr/lib/x86_64-linux-gnu
 # ln -s libcudart.so.10.1 libcudart.so.10.0
 # ln -s libcublas.so libcublas.so.10.0
 # ln -s libcufft.so libcufft.so.10.0
 # ln -s libcurand.so libcurand.so.10.0
 # ln -s libcusolver.so libcusolver.so.10.0
 # ln -s libcusparse.so libcusparse.so.10.0

これで、チュートリアルを正常に実行できます

 2019-07-24 21:43:21.172908: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
 2019-07-24 21:43:21.174653: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
 2019-07-24 21:43:21.175826: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
 2019-07-24 21:43:21.182305: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
 2019-07-24 21:43:21.183970: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
 2019-07-24 21:43:21.206796: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
 2019-07-24 21:43:21.210685: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
 2019-07-24 21:43:21.212694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
 2019-07-24 21:43:21.213060: I tensorflow/core/platform/cpu_feature_guard.cc:142]      
 Your CPU supports instructions that this TensorFlow binary was not compiled to use: FMA
 2019-07-24 21:43:21.238541: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3214745000 Hz
 2019-07-24 21:43:21.240096: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x557e2b682ce0 executing computations on platform Host. Devices:
 2019-07-24 21:43:21.240162: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): <undefined>, <undefined>
 2019-07-24 21:43:21.355158: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x557e2b652000 executing computations on platform CUDA. Devices:
 2019-07-24 21:43:21.355234: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): GeForce GTX 1060 6GB, Compute Capability 6.1
 2019-07-24 21:43:21.357074: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
 name: GeForce GTX 1060 6GB major: 6 minor: 1 memoryClockRate(GHz): 1.7715
 pciBusID: 0000:01:00.0
 2019-07-24 21:43:21.357151: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
 2019-07-24 21:43:21.357207: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
 2019-07-24 21:43:21.357245: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
 2019-07-24 21:43:21.357283: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
 2019-07-24 21:43:21.357321: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
 2019-07-24 21:43:21.357358: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
 2019-07-24 21:43:21.357395: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
 2019-07-24 21:43:21.360449: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
 2019-07-24 21:43:21.380616: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
 2019-07-24 21:43:21.385223: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 Edge matrix:
 2019-07-24 21:43:21.385272: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0 
 2019-07-24 21:43:21.385299: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N 
 2019-07-24 21:43:21.388647: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5250 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:01:00.0, compute capability: 6.1)
 2019-07-24 21:43:32.001598: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
 2019-07-24 21:43:32.532105: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
 W0724 21:43:34.981204 140284114071872 deprecation_wrapper.py:119] From classify_image.py:85: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.
0
Alex Volkov

問題の原因は、現在のcudaバージョン10.1です（画像の右上隅から確認できます）。

公式のTF Webサイトからわかるように、tfとcudaの対応は次のとおりです チャートのTF Webサイト

Version                 cuDNN    CUDA
tensorflow-2.1.0         7.6       10.1
tensorflow-2.0.0         7.4       10.0
tensorflow_gpu-1.14.0    7.4       10.0
tensorflow_gpu-1.13.1    7.4       10.0

したがって、tfを2.1にアップグレードするか、次のコマンドでcudaをダウングレードできます。

conda install cudatoolkit=10.0.130

次に、自動的にcudnnもダウングレードします。

0
Wey Shi

Tensorflowのバージョンを変更すると問題が解決しました。

この問題を確認してください 1https://github.com/tensorflow/tensorflow/issues/26182 ）

公式のtensorflow-gpuバイナリ（pipまたはcondaによってダウンロードされたもの）は、cuda 9.0、TF 1.5以降のcudnn 7、およびTF 1.13以降のcuda 10.0、cudnn 7でビルドされています。これらはリリースノートに書かれています。公式のバイナリを使用する場合は、対応するバージョンのcudaを使用する必要があります。

0
Lynne