最近在学习google新开源的深度学习框架tensorflow。发现安装它的时候,需要依赖python2.7.X;我之前一直使用的linux是centos。而centos不更新了,里面的自带的python一般都是python2.6以下的。不仅如此,系统里面很多组件又依赖python2.6,所以导致你都不能替换掉它。无奈之下,选择ubuntu了。下面介绍一下使用ubuntu安装tensorflow遇到的一些问题。
1、ubuntu无法用Winscp连接
解决办法:
(1)、采用桥接的方式进行上网(由于是用虚拟机安装的操作系统)
(2)、利用ps -e |grep ssh 查看是否有sshd进程开启。如果没有则需要安装openssh-server
安装的方式:sudo apt-get install openssh-server
启动相应的进程:/etc/init.d/ssh start
(3)、此时需要reboot系统
(4)、由于ubuntu最初root的用户是没有被激活的,所以需要通过修改root用户密码来激活root用户。
完成即可连接了。
2、安装tensorflow。
由于我的ubuntu是最新版的(ubuntu-16.04-desktop-amd64),里面自带的python是2.7.11。因此满足要求。由于tensorflow有三种安装方式,这里采用的是pip安装方式。下面开始安装tensorflow:
(1)首先安装pip
sudo apt-get install python-pip python-dev
(2)利用pip安装tensorflow
sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64.whl
安装好了后,如下图所示:
根据上面黄色的提示,叫我升级pip:于是我就按照他的要求升级了,执行:pip install --upgrade pip
3、检验tensorflow是否安装成功
通过下面一段代码来测试tensorflow是否安装成功:
$ python
...
>>> 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
>>>
下面是我执行的结果如下图所示:
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA5oAAAE3CAIAAABEiqnFAAAgAElEQVR4nO3d3bmrKhSFYeuxFSuxEAuhjhS394Ux4WdOmCgqZn3vcy7OziKIaJIRgjgMiXF2rzc3j+nfS7znv5ap/vmPNc6uuMOWMsBT1JzP4+xebj63PQAAYLdpefnE7wGWMsBTGM9n79stZz4AAAAAAAAAAAAAAAAAAAAAAAAAAACAnO0q5qcuMnVk8bCn73tD0/KEy9K3peI4YAAAIHT5mqmtwtPsXt8FL6dlT8557L635a/NdG9YLPYPC/wCAIDEQyNdkl/3VPvQfW/nPeL57oN93wlaIs4CAIB6z4x0s4srIc7W6vB+TsRZAADgSSaHfu9T6yeCLdL5d7ENCljq2R5y85i5nW56J6G4mLHNYez5/FZeXc8j913Y7D7Hs7Xf5GAH44OVPh4/WO6fYRi2OFu+Y3N4b6ugObbjBQAAepGOZsUjkuPsXovz56FG01KN9azxaFm+w6bj7KQktmMELtnWt45peTc1rfZH991r5/E8e3ys89OHXk2fg/KRjqYPUm9Y+sc5b1BZ6udpEb6UCBsyHC8AAHA/W6QTPsmjYGGMdFFsEKNYyzjr/WFvnH3cvgdtLw5PFsJuMIq5K86Na/6PtzLOLngwjc6jEHEt/RMF5bh/pkWcQZGWshwvAABwP1ukkyJEGAusI5RhRU+Is4/bdwNvOPKb/4oDkMmoponWh+PssgO04tDw8f7RaigWI84CANAp4w/uyujf9/HOIt2njm9w2z3Z4Gn7Xs04ULtzW7Y+3NqxPaKE4OP9o+0BcRYAgKf60RFKvw511dQf3fdGpHr3xlnT6OzgDdBqs3YZnQUAALGL549eFumUDFVZzzP33W/7/ivB0n3XgqmhnvLc2dUaY/UNNegf89xZ4iwAAM8QfUiHy+Z/SxSvTC/XY44I8RzO5Kocy7a01FLX5ofu+zAMx1c2CBYnO1CT1IdrXhWLz+vSBEpwLPaP8atF8csPcRYAgCcJYoub/VE9f93Q4jXumXrCbLQ+2a9PuIA9v7Hctvwyn6cqA36/uu/D8dHZcIv7g9wWA4P9ynzTKF1wpvZP2KnCQ6NWSbqEQcXxAgAAOFEaTLBDkzhbUbyzW5EBAADg2S6Ms03u3AAAAAC0UhNnGZoFAABAR3JTVD2NLjoDAAAAAAAAAAAAAAAAAAAAAAAAAAAAAPxh252WultS1L8F1L4looSbwR7b1XU5gPzTLWXaKy8K2+BWZNFqCCfspHDbL6Qy51jbc972GvTOC30z5teFvwMnLqNhbs9a8EhLLP1j6sMi2/HyCknbYoFpAA21/VRKb3Mf6e6m9+H9VEt3V83UEj+r8k5Yb9vRWGb96ZYyJzEvCls8EUrbuGqRrvxhOrAblW04O79XMpxjzc5542vQDz/ieVjxupiWcyNsbXuG9y65A6d+sX+MZWxbKh+v2XlJV0muwU3IAeC45GN75xfnp8VZYTdbDRkcDGWWZNCqjNm0WEPA/hzYtMFHN3dNnPU391qmrgatqg7HrnPe9hqclih7ZQ5Noc0Xn2G2DX4O/c7zzdI/NX1YaqnhoSgrC19/GKAF0JrwvjbOrv67+9Pi7DAvyT6mb8Q7HB5i7DDOjhVjKcTZHbbP9p4+4ysOx95z3vIaFLKQ/jrNt3l2V9+go9yHW9ftPt8s/VPVhxmW4zUKvazmWW6YAqAZOc6+333E2Vbxg8qchbjatVLv11XlrSycPRm8C/pzM8sVVWsSp47fqbXDOJtJs8Hheiey+ICEZ4jyy6NAPPjfoy624/Ocb3ml5Vr/GM/nhrxzJs6z/m4FDRPiSdDMrfD+VtvPn4Z3J043KqQjvWW5Nu/6ln5QsQ8/3wMKQ876obT0j70Pa6e/p9UocVaocM2zps0AQFHxlylx4CV9lmV0dp0g9v63NOKXTMYSvsFPy8sty7dRNSOHOY3S3/Hxtf7irDqOEnX9tLxezoUngnhI9UuMzA0WD3taQabOfkZn/ZeYcP6Ms3stTujqNAqsrfaO14HT0X44mo0pC5uUjsO+OPseIvS+f52fpQp96HVc5nz7fI2RClj6p6IPs9tKiJWk477aWzTjswAaKs+dTT+spN8WLXE2/VkqfdcVn5jEoWBTDXJbs4uQGnyydxdnlU8jaRhmLft9WG5DZmSopsFp8UfG2ejck19uQmOUYbDMeHR9u0wVNUqz8muwWZwdZ/daFv+7VMNBZU1p8kPwNWbX6GzjOFsxOqu/Z/rvF+vbtRM3tvfyWwAQxCsjSe8v0fuW+PG1Y+5s9I6q1VAsdjS3NbygvsUn+5Gomh5N9dd5O3kQRTtcwePartSkXNVvxNkkVCXnkHZ+Cr+et5x7az0cTbapvgabxVkx6Y+zOzVOFUaLwylcu863xnHWqvSe6U2Mec+T0bIzcRZAG6a30XSVF2ki1ME4q72/nhtnG2bZhp/sXY3OHouzerqWRnYzDY4nzwpfvZ4YZ+Uu8humNdT40/xexvOn0e8RarOFVuwenZWvej3xKGfak44R7GuJpX+q+rCs/j1T7mbiLICGjG+j/iUL2rjg80Znm2bZ4fASXasu46x9ON40OisqDWWVw+vz4qx4BkavsbrR2avj7NFzvvQatCw7FVSWO4X6ibPK7yj1L1hL/1T1YcGO98zsb0nEWQBtWD8A149Y/b3seJy1z51tE2fNFyJY55OV3uiN9XQXZ5WessydlZfoUeR/KU631UOc3cZWd3a0Mn0zzLN1c2evjbMHvxBaXoPJKVSYZlpzTMXT8+Axtbcn37agksz7hqV/zH1Y3lb94c5Gei4FA9CI/QNwdtqU/mFIfzhKrtiyRI106Df9tGwTZ8V3UiV7zbarfYtXllTU01ecVRfqio7OOLtkZQPxGnw1H+fOLr+S7VM3f0a9S+2Ks8XzOdMMM/WH+uAP45yubKDn4Evj7KGrqcyvwWCvssOKlvkqn7/Lq0McPaY17fHsXdkgea7SP8Y+zG2r5j0z+5zgb/pzAcBGmIuYf3Mp/TYU/n4WR4FwE+FDo1ZJ+LegxWv9aj3V+673gHFUtThOla9HaVE8B65YJthcozibmeQWNMnN3yOSxkqtxdrBSH4wDf42Dp/uzLQn7nP9Wrl099TzOSpx4H6hae1jvAPfAxk8I10kxLZTRVU1HRmbrXoNemWFltS02etF8cAdOaZ72pNfTngYbO8/+f6xl8lsy3q8yi+bbznGZgHc4NBIDJ6Nzx7B+sF9+uS/ht9LUHLRMUXLRTgAoAJvP38aX2YS7/kHp2+HOHudq47pn8eiBgDuQZr58/g+E7psmSHi7GVYOuoavJcAuJg0vZZfnIGL5KaSAwAAAAAAAAAAAAAAAAAAAAAAAAAAAMCjeHd86f7iaenuNDsXfQmqOrbjTZZf99ujL4vmXe2ev+eOqT35LjBtyyupdmKxPcVjMVruatQX4TZ2qtI9965kOw8BAOiL5V7nftYQyqd350xv520pc7StVrMLY9PeOLHt0jIfbFfYAK05/oqN4mLAFe15rxmvpvjitr7G2b2ck255amlP1bF44jKshjZ3E2dt5yEAAN3JfNyOs4syzzugeOXXmOpXsK/M0bYec7DiY08XFhaXHwoz5bSoedTwFSXb3JptrU3NFLBs0Fj4R+NsJ2znIQAAHVI/bpU/BA8rZYJPQUuZo2096tY4O8xLMvYpBcp4C0kZY3tmV5hcUbGtdeR2zOXdYnvshZ8TDb8e1GbLeQgAQI+0j9t8QGlbxuqkaDAtB6fPNm9XWqGQQfWt5tozzq4UUOzbmrc5Bs3ibPZYNOjn8F5bQWXbfBg3jw1nlJd+/dDn11ras+1O8OUxqTCZBm2dF/2gLA4A+NO0TyzLB1mrMlbj7NaJmE2ixveT/2jebvypL1QnxcV9cfY99OoFmjjdmrflDbAfjbO2Y3Gwn5PJoEJ2npaXW5bvTOBxdsd+b7e0OVPG0h55Nnv4UDoBepamO1c3HQCAHuhzAbobnH2HHu9TufyRbHD8kpeWn/ujuE/N4uw4u9ey+HucBB3rtvyGthqdzR+LQ/2s/G4eVZleI3fBRJR8nC22xxJnh/BA27Js90udAACwssXZ8Dfa9wfs5XFWrr9BkCxcvG95epM4q2aIZnH2fSCTobvwp2nDtsK5z43nzu6aE5yntTCqMy12e5wttscYZ4etb8myAIBfUzvZwC9/9WQDQau4fKieNnE2myGELewenU22MoazZS3bitraMM5mKjvSz8YrHn87zq6FC9/cyLIAgMepvRTML9/B8OyvxNlShhDat29lA+laqyjOGrYVj9bnryvqIc4yOjtsX0Jyv0WQZQEAT5RbqEv6zAvLKyEh+CXaUmZvQ5VK/IvCrXVrO2uo52ictSytkMyq2L3ubPrEuO6abVkK9DDZwD539lfjrB9U5U4+vMQHAAD3KPwwLd56yi+fDOcI9zS1lDE2NZqwqVSSu04++bk9rtZYT1TlkZiVVi9NCQ6STXZB0EJ7wqvj1+3v3pZQ3t6emmORq8cm/e6TDkU+Mc5Gj7y/g8VfUKR6onFp23kIAEB38h+33wWUMmtjRYXU9fZLZazNLa/TVRxVDVuTvZReryfpm0Jt5R0qdZFXVthKTXsyC3WZtiVvNAmLlvYYj8XQYlJHNEkiWTIgaoZfvGbYUpmL8Uq+jOXK1LQn6EM3B+etrZ6q8xAAgL6wuCSegnMVAAAIiAh4Cs5VAAAg8H5k5CoQdGk0TnwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD4s7abGS2TdMOu7ZEmSzkJt1I6o81tXbmtG+g3NS5qem5wTD+yLTpwvOz67h+Zoc017z+X9POVmh/T+A58v9RZ12h3jv3msfi51+Bz6LfX7PyT4P3WtrbxvRfRKdR8of2jS/cb2tzMldu6wdG3DOORnJbSq4BjGtA6rHC8yv1s8YD+SdS02fD+83MfpW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4、安装python-numpy ,python-scipy,python-matplotlib
sudo apt-get install python-numpy
sudo apt-get install python-scipy
sudo apt-get install python-matplotlib
验证是否安装成功:(如下图所示)