TensorFlow入门——安装（带GPU）

这一系列基本上是属于我自己进行到了那个步骤就做到那个步骤的

由于新装了GPU (GTX750ti)和CUDA9.0、CUDNN7.1版本的软件，所以希望TensorFlow能在GPU上运行，也算上补上之前的承诺

说了下初衷，由于现在新的CUDA版本对TensorFlow的支持不好，只能采取编译源码的方式进行

所以大概分为以下几个步骤

1.安装依赖库（这部分我已经做过了，不进行介绍，可以看前边的依赖库，基本一致）

2.安装Git（有的就跳过这一步）

3.安装TensorFlow的build工具bazel

4.编译TensorFlow源码

5.安装并配置环境变量

1.安装依赖库

2.安装Git

使用

sudo apt-get install git

3. 安装TensorFlow的build工具bazel

这一步比较麻烦，是因为apt-get中没有bazel这个工具

因此需要到GitHub上先下载，再进行安装 下载地址是https://github.com/bazelbuild/bazel/releases

选择正确版本下载，并使用sudo命令安装.sh文件即可

4.编译TensorFlow源码

这一步特别麻烦，有很多选项需要选择，我的选择如下：

 1 [email protected]:~/tools/tensorflow$ ./configure
 2 WARNING: Running Bazel server needs to be killed, because the startup options are different.
 3 You have bazel 0.14.1 installed.
 4 Please specify the location of python. [Default is /usr/bin/python]:
 5
 6
 7 Found possible Python library paths:
 8   /usr/local/lib/python2.7/dist-packages
 9   /usr/lib/python2.7/dist-packages
10 Please input the desired Python library path to use.  Default is [/usr/local/lib/python2.7/dist-packages]
11
12 Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]: Y
13 jemalloc as malloc support will be enabled for TensorFlow.
14
15 Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]: n
16 No Google Cloud Platform support will be enabled for TensorFlow.
17
18 Do you wish to build TensorFlow with Hadoop File System support? [Y/n]: n
19 No Hadoop File System support will be enabled for TensorFlow.
20
21 Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: n
22 No Amazon S3 File System support will be enabled for TensorFlow.
23
24 Do you wish to build TensorFlow with Apache Kafka Platform support? [Y/n]: n
25 No Apache Kafka Platform support will be enabled for TensorFlow.
26
27 Do you wish to build TensorFlow with XLA JIT support? [y/N]: y
28 XLA JIT support will be enabled for TensorFlow.
29
30 Do you wish to build TensorFlow with GDR support? [y/N]: y
31 GDR support will be enabled for TensorFlow.
32
33 Do you wish to build TensorFlow with VERBS support? [y/N]: y
34 VERBS support will be enabled for TensorFlow.
35
36 Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: N
37 No OpenCL SYCL support will be enabled for TensorFlow.
38
39 Do you wish to build TensorFlow with CUDA support? [y/N]: y
40 CUDA support will be enabled for TensorFlow.
41
42 Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 9.0]: 8
43
44
45 Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
46
47
48 Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]:
49
50
51 Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
52
53
54 Do you wish to build TensorFlow with TensorRT support? [y/N]: N
55 No TensorRT support will be enabled for TensorFlow.
56
57 Please specify the NCCL version you want to use. [Leave empty to default to NCCL 1.3]:
58
59
60 Please specify a list of comma-separated Cuda compute capabilities you want to build with.
61 You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
62 Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 5.0]
63
64
65 Do you want to use clang as CUDA compiler? [y/N]: N
66 nvcc will be used as CUDA compiler.
67
68 Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
69
70
71 Do you wish to build TensorFlow with MPI support? [y/N]: N
72 No MPI support will be enabled for TensorFlow.
73
74 Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:
75
76
77 Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: N
78 Not configuring the WORKSPACE for Android builds.
79
80 Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See tools/bazel.rc for more details.
81     --config=mkl             # Build with MKL support.
82     --config=monolithic      # Config for mostly static monolithic build.
83 Configuration finished

然后使用bazel进行编译(本步骤非常容易出问题，而且特别耗时)

bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package

bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg

5.安装并配置环境变量

使用pip进行安装

$ sudo pip install /tmp/tensorflow_pkg/tensorflow

# with no spaces after tensorflow hit tab before hitting enter to fill in blanks

最后就是测试

import tensorflow as tf
sess = tf.InteractiveSession()
sess.close()

如果每一步都不报错的，TensorFlow就编译并安装成功了

原文地址：https://www.cnblogs.com/jourluohua/p/9180709.html