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  • tensorflow的Virtualenv安装方式安装

     本文介绍了如何在ubuntu上以virtualenv方式安装tensorflow。  

    安装pip和virtualenv:

    # Ubuntu/Linux 64-bit
    sudo apt-get install python-pip python-dev python-virtualenv
    
    # Mac OS X
    sudo easy_install pip
    sudo pip install --upgrade virtualenv
    

     创建 Virtualenv 虚拟环境:

      进入你想安装tensorflow的父目录下,然后执行下面命令建立虚拟环境:

    virtualenv --system-site-packages tensorflow
    

     激活虚拟环境并安装tensorflow:

      对于python27,则执行如下命令:

    source ./tensorflow/bin/activate  # If using bash
    source ./tensorflow/bin/activate.csh  # If using csh
    (tensorflow)$  # Your prompt should change
    
    # Ubuntu/Linux 64-bit, CPU only:
    pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.6.0-cp27-none-linux_x86_64.whl
    
    # Ubuntu/Linux 64-bit, GPU enabled:
    pip install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.6.0-cp27-none-linux_x86_64.whl
    
    # Mac OS X, CPU only:
    pip install --upgrade https://storage.googleapis.com/tensorflow/mac/tensorflow-0.6.0-py2-none-any.whl
    

       对于python3则执行如下命令:

    source ./tensorflow/bin/activate  # If using bash
    source ./tensorflow/bin/activate.csh  # If using csh
    (tensorflow)$  # Your prompt should change
    
    # Ubuntu/Linux 64-bit, CPU only:
    pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.6.0-cp34-none-linux_x86_64.whl
    
    # Ubuntu/Linux 64-bit, GPU enabled:
    pip install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.6.0-cp34-none-linux_x86_64.whl
    
    # Mac OS X, CPU only:
    pip3 install --upgrade https://storage.googleapis.com/tensorflow/mac/tensorflow-0.6.0-py3-none-any.whl
    

     测试安装:

      在终端执行如下命令进入python shell环境:

    python
    

       在python shell环境中测试:

    >>> import tensorflow as tf
    >>> hello = tf.constant('Hello, TensorFlow!')
    >>> sess = tf.Session()
    >>> print(sess.run(hello))
    Hello, TensorFlow!
    >>> a = tf.constant(10)
    >>> b = tf.constant(32)
    >>> print(sess.run(a + b))
    42
    >>>
    
    •  如果遇到如下错误:
        _mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
    ImportError: libcudart.so.7.0: cannot open shared object file: No such file or directory
    

       那是你的CUDA安装配置不对:

        安装CUDA和CUDNN可以参考 这篇文章

      且添加如下两行到你的 ~/.bashrc 文件

    export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"
    export CUDA_HOME=/usr/local/cuda
    
    •  如果遇到如下错误:
    Python 2.7.9 (default, Apr  2 2015, 15:33:21) 
    [GCC 4.9.2] on linux2
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import tensorflow
    I tensorflow/stream_executor/dso_loader.cc:93] Couldn't open CUDA library libcublas.so.7.0. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
    I tensorflow/stream_executor/cuda/cuda_blas.cc:2188] Unable to load cuBLAS DSO.
    I tensorflow/stream_executor/dso_loader.cc:93] Couldn't open CUDA library libcudnn.so.6.5. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
    I tensorflow/stream_executor/cuda/cuda_dnn.cc:1382] Unable to load cuDNN DSO
    I tensorflow/stream_executor/dso_loader.cc:93] Couldn't open CUDA library libcufft.so.7.0. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
    I tensorflow/stream_executor/cuda/cuda_fft.cc:343] Unable to load cuFFT DSO.
    I tensorflow/stream_executor/dso_loader.cc:101] successfully opened CUDA library libcuda.so locally
    I tensorflow/stream_executor/dso_loader.cc:93] Couldn't open CUDA library libcurand.so.7.0. LD_LIBRARY_PATH: :/usr/local/cuda/lib64
    I tensorflow/stream_executor/cuda/cuda_rng.cc:333] Unable to load cuRAND DSO.
    

       由安装报错可知,它使用的是7.0版本,故找不到,而如果你安装的是7.5版本,则可以执行如下命令添加相应链接:

    sudo ln -s /usr/local/cuda/lib64/libcudart.so.7.5 /usr/local/cuda/lib64/libcudart.so.7.0
    sudo ln -s libcublas.so.7.5 libcublas.so.7.0
    sudo ln -s libcudnn.so.4.0.4 libcudnn.so.6.5
    sudo ln -s libcufft.so libcufft.so.7.0
    sudo ln -s libcurand.so libcurand.so.7.0
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  • 原文地址:https://www.cnblogs.com/simplelovecs/p/5149982.html
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