linux下安装TensorFlow(centos)

1、python安装

  centos自带python2.7.5,这一步能够省略掉。python

2、python-pip

  pip--python index package,累世linux的yum,安装管理python软件包用的。linux

yum install  python-pip python-devel

 

3、安装tensorflow

  安装基于linux和python2.7的tensorflow 0.9centos

pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl

  其余操做系统版本能够参照下表:api

  

# Ubuntu/Linux 64-bit, CPU only, Python 2.7
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
# Requires CUDA toolkit 7.5 and CuDNN v4. For other versions, see "Install from sources" below.
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl

# Mac OS X, CPU only, Python 2.7:
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/tensorflow-0.9.0-py2-none-any.whl

# Ubuntu/Linux 64-bit, CPU only, Python 3.4
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.9.0-cp34-cp34m-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
# Requires CUDA toolkit 7.5 and CuDNN v4. For other versions, see "Install from sources" below.
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0-cp34-cp34m-linux_x86_64.whl

# Ubuntu/Linux 64-bit, CPU only, Python 3.5
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.9.0-cp35-cp35m-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 3.5
# Requires CUDA toolkit 7.5 and CuDNN v4. For other versions, see "Install from sources" below.
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0-cp35-cp35m-linux_x86_64.whl

# Mac OS X, CPU only, Python 3.4 or 3.5:
 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/tensorflow-0.9.0-py3-none-any.whl

4、测试安装是否成功

  编写python脚本 test.pypython2.7

import tensorflow as tf
hello = tf.constant('Hello,TensorFlow!')
sess = tf.Session()
print(sess.run(hello))
a = tf.constant(10)
b = tf.constant(32)
print(sess.run(a + b))

运行 python test.py结果以下:测试

大功告成。ui

参考:http://blog.csdn.net/chuchus/article/details/51713389google

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