本文介紹了如何在ubuntu上以virtualenv方式安裝tensorflow。
安裝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
創建 Virtualenv 虛擬環境:
進入你想安裝tensorflow的父目錄下,然后執行下面命令建立虛擬環境:
virtualenv --system-site-packages tensorflow
激活虛擬環境並安裝tensorflow:
對於python27,則執行如下命令:
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
對於python3則執行如下命令:
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
測試安裝:
在終端執行如下命令進入python shell環境:
python
在python shell環境中測試:
>>> 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
>>>
- 如果遇到如下錯誤:
_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安裝配置不對:
安裝CUDA和CUDNN可以參考 這篇文章 。
且添加如下兩行到你的 ~/.bashrc 文件
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64" export CUDA_HOME=/usr/local/cuda
- 如果遇到如下錯誤:
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.
由安裝報錯可知,它使用的是7.0版本,故找不到,而如果你安裝的是7.5版本,則可以執行如下命令添加相應鏈接:
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
