全網最詳細的基於Ubuntu14.04/16.04 + Anaconda2 / Anaconda3 + Python2.7/3.4/3.5/3.6安裝Tensorflow詳細步驟（圖文）（博主推薦）
很少說，直接上乾貨！html
前言html5
建議參照最新的tensorflow安裝步驟（Linux，官方網站常常訪問不是很穩定，因此給了一個github的地址）： https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/install/install_linux.mdnode
最近，tensorflow網站上給出了新的使用Anaconda配置和安裝Tensorflow的步驟，通過測試，在國內能夠無障礙的訪問。Anaconda 是一個基於python的科學計算包集合，目前支持Python 2.7，3.4，3.5，3.6。python
注意：在安裝過程當中若是出現很長的報錯，觀察錯誤信息的末尾，若是是網絡連接相關，就從新運行一遍語句便可（如出現進度條不動的狀況，也可從新運行語句），Anaconda自身約500M，tensorflow所需軟件包約幾十Ｍ。linux
操做系統： Ubuntu 14.04 或 Ubuntu16.04git
這是Github官網給出的安裝步驟github
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/install/install_linux.mdweb
第一步、 安裝Anaconda
從anaconda官網（https://www.continuum.io/downloads）上下載linux版本的安裝文件，運行完成安裝。redis
我這裏是以Anaconda2-5.0.1-Linux-x86_64.sh爲例，Anaconda3同樣啦。這個很簡單。sql
deeplearning@deeplearningsinglenode:~/SoftWare$ pwd /home/deeplearning/SoftWare deeplearning@deeplearningsinglenode:~/SoftWare$ ll total 519916 drwxrwxr-x 4 deeplearning deeplearning 4096 12月 4 09:42 ./ drwxr-xr-x 17 deeplearning deeplearning 4096 12月 3 20:46 ../ -rwxrw-r-- 1 deeplearning deeplearning 532375438 12月 4 09:42 Anaconda2-5.0.1-Linux-x86_64.sh* drwxr-xr-x 8 deeplearning deeplearning 4096 8月 5 2015 jdk1.8.0_60/ drwxrwxr-x 11 deeplearning deeplearning 4096 12月 3 20:07 pycharm-2017.3/ deeplearning@deeplearningsinglenode:~/SoftWare$ bash ./Anaconda2-5.0.1-Linux-x86_64.sh Welcome to Anaconda2 5.0.1 In order to continue the installation process, please review the license agreement. Please, press ENTER to continue >>> =================================== Anaconda End User License Agreement =================================== Copyright 2015, Anaconda, Inc. All rights reserved under the 3-clause BSD License: Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditio ns are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of Continuum Analytics, Inc. (dba Anaconda, Inc.) ("Continuum") nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT N OT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL CON TINUUM BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY TH EORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Notice of Third Party Software Licenses ======================================= Anaconda contains open source software packages from third parties. These are available on an "as is" basis and subject to their in dividual license agreements. These licenses are available in Anaconda or at https://docs.anaconda.com/anaconda/packages/pkg-docs . Any binary packages of these third party tools you obtain via Anaconda are subject to their individual licenses as well as the Anac onda license. 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Please answer 'yes' or 'no':' >>> yes Anaconda2 will now be installed into this location: /home/deeplearning/anaconda2 - Press ENTER to confirm the location - Press CTRL-C to abort the installation - Or specify a different location below [/home/deeplearning/anaconda2] >>> PREFIX=/home/deeplearning/anaconda2
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Do you wish the installer to prepend the Anaconda2 install location to PATH in your /home/deeplearning/.bashrc ? [yes|no] [no] >>> You may wish to edit your .bashrc to prepend the Anaconda2 install location to PATH: export PATH=/home/deeplearning/anaconda2/bin:$PATH Thank you for installing Anaconda2!
由於這是一個坑，是安裝時最後一步添加環境變量的時候沒有選擇yes致使運行 conda info 時出錯，很好解決，根據錯誤提示：
而後，緊接着去配置Anaconda2的環境變量。怎麼作呢？很簡單。
在命令行輸入就能夠了。
$ export PATH=/home/deeplearning/anaconda2/bin:$PATH
第二步、創建一個tensorflow的運行環境
# Python 2.7 （選好本身的） $ conda create -n tensorflow python=2.7 # Python 3.4 （選好本身的） $ conda create -n tensorflow python=3.4 # Python 3.5 （選好本身的） $ conda create -n tensorflow python=3.5
注意：在這一步，你也許會遇到conda: command not found
遇到這個問題的時候，
解決方法是：
export PATH="/home/[your_name]/anaconda/bin:$PATH"
好比我這裏是
export PATH=/home/deeplearning/anaconda2/bin:$PATH
可是下一次重啓以後，仍是會出現這個問題，因此咱們要激活下 ~/.bash_profile
. ~/.bash_profile
#或者
source ~/.bash_profile
或者source /etc/profile
那是由於個人環境變量是以下：
#Anaconda2 ANACONDA2_HOME=/home/deeplearning/anaconda2 ANACONDA2_BIN=/home/deeplearning/anaconda2/bin PATH=$PATH:$ANACONDA2_BIN export ANACONDA2_HOME ANACONDA2_BIN PATH
因此，
deeplearning@deeplearningsinglenode:~$ conda create -n tensorflow python=2.7 Fetching package metadata ........... Solving package specifications: . Package plan for installation in environment /home/deeplearning/anaconda2/envs/tensorflow: The following NEW packages will be INSTALLED: ca-certificates: 2017.08.26-h1d4fec5_0 certifi: 2017.11.5-py27h71e7faf_0 libedit: 3.1-heed3624_0 libffi: 3.2.1-hd88cf55_4 libgcc-ng: 7.2.0-h7cc24e2_2 libstdcxx-ng: 7.2.0-h7a57d05_2 ncurses: 6.0-h9df7e31_2 openssl: 1.0.2m-h26d622b_1 pip: 9.0.1-py27ha730c48_4 python: 2.7.14-hdd48546_24 readline: 7.0-ha6073c6_4 setuptools: 36.5.0-py27h68b189e_0 sqlite: 3.20.1-hb898158_2 tk: 8.6.7-hc745277_3 wheel: 0.30.0-py27h2bc6bb2_1 zlib: 1.2.11-ha838bed_2 Proceed ([y]/n)? y
第三步、在conda環境中安裝tensorflow
在conda環境中安裝tensorflow的好處是能夠便捷的管理tensorflow的依賴包。
分爲兩個步驟：激活上一步創建的名爲tensorflow的conda環境；用conda或者pip工具安裝Tensorflow，我選擇的是pip方式。
3.1 pip方式（能夠這種方式來安裝）
pip方式須要首先激活conda環境
deeplearning@deeplearningsinglenode:~$ source activate tensorflow
(tensorflow) deeplearning@deeplearningsinglenode:~$
而後根據要安裝的不一樣tensorflow版本選擇對應的一條環境變量設置export語句（操做系統，Python版本，CPU版本仍是CPU+GPU版本）
# Ubuntu/Linux 64-bit, CPU only, Python 2.7 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7 # Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below. (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl # Mac OS X, CPU only, Python 2.7: (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.10.0-py2-none-any.whl # Mac OS X, GPU enabled, Python 2.7: (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow-0.10.0-py2-none-any.whl # Ubuntu/Linux 64-bit, CPU only, Python 3.4 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp34-cp34m-linux_x86_64.whl # Ubuntu/Linux 64-bit, GPU enabled, Python 3.4 # Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below. (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp34-cp34m-linux_x86_64.whl # Ubuntu/Linux 64-bit, CPU only, Python 3.5 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5 # Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below. (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl # Mac OS X, CPU only, Python 3.4 or 3.5: (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.10.0-py3-none-any.whl # Mac OS X, GPU enabled, Python 3.4 or 3.5: (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow-0.10.0-py3-none-any.whl
最後根據是python 2仍是３版本選擇一句進行安裝。
# Python 2 (tensorflow)$ pip install --ignore-installed --upgrade $TF_BINARY_URL # Python 3 (tensorflow)$ pip3 install --ignore-installed --upgrade $TF_BINARY_URL
(tensorflow) deeplearning@deeplearningsinglenode:~$ pip install --ignore-installed --upgrade $TF_BINARY_URL Collecting tensorflow==0.10.0 from https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl Downloading https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl (36.6MB) 12% |████ | 4.5MB 14.0MB/s eta 0:00:03^[^A^[^AException: Traceback (most recent call last): File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/basecommand.py", line 215, in main status = self.run(options, args) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/commands/install.py", line 335, in run wb.build(autobuilding=True) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/wheel.py", line 749, in build self.requirement_set.prepare_files(self.finder) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/req/req_set.py", line 380, in prepare_files ignore_dependencies=self.ignore_dependencies)) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/req/req_set.py", line 620, in _prepare_file session=self.session, hashes=hashes) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/download.py", line 821, in unpack_url hashes=hashes File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/download.py", line 659, in unpack_http_url hashes) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/download.py", line 882, in _download_http_url _download_url(resp, link, content_file, hashes) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/download.py", line 605, in _download_url consume(downloaded_chunks) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/utils/__init__.py", line 852, in consume deque(iterator, maxlen=0) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/download.py", line 571, in written_chunks for chunk in chunks: File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/utils/ui.py", line 139, in iter for x in it: File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/download.py", line 560, in resp_read decode_content=False): File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/_vendor/requests/packages/urllib3/response.py", line 357, in stream data = self.read(amt=amt, decode_content=decode_content) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/_vendor/requests/packages/urllib3/response.py", line 324, in read flush_decoder = True File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/contextlib.py", line 35, in __exit__ self.gen.throw(type, value, traceback) File "/home/deeplearning/anaconda2/envs/tensorflow/lib/python2.7/site-packages/pip/_vendor/requests/packages/urllib3/response.py", line 246, in _error_catcher raise ReadTimeoutError(self._pool, None, 'Read timed out.') ReadTimeoutError: HTTPSConnectionPool(host='storage.googleapis.com', port=443): Read timed out. (tensorflow) deeplearning@deeplearningsinglenode:~$
注意：這是在安裝tensorflow的時候建立tensorflow環境失敗，這是個坑，由於有些版本地址失效了。
換其餘版本試試。好比以下我如今是2017年12月份，採用conda方式安裝tensorflow，版本已是1.4.0-py27_0
3.2 conda方式（或者也能夠這種方式來安裝）
conda上面目前有人已經作好了tensorflow的pkg，可是版本不必定最新，且只有CPU版本，不支持GPU。
步驟也是首先激活conda環境，而後調用conda install 語句安裝.
$ source activate tensorflow (tensorflow)$ # Your prompt should change # Linux/Mac OS X, Python 2.7/3.4/3.5, CPU only: (tensorflow)$ conda install -c conda-forge tensorflow
(tensorflow) deeplearning@deeplearningsinglenode:~$ conda install -c conda-forge tensorflow Fetching package metadata ............. Solving package specifications: . Package plan for installation in environment /home/deeplearning/anaconda2/envs/tensorflow: The following NEW packages will be INSTALLED: bleach: 1.5.0-py27_0 conda-forge enum34: 1.1.6-py27_1 conda-forge funcsigs: 1.0.2-py_2 conda-forge futures: 3.2.0-py27_0 conda-forge html5lib: 0.9999999-py27_0 conda-forge intel-openmp: 2018.0.0-hc7b2577_8 markdown: 2.6.9-py27_0 conda-forge mkl: 2018.0.1-h19d6760_4 mock: 2.0.0-py27_0 conda-forge numpy: 1.13.3-py27hbcc08e0_0 pbr: 3.1.1-py27_0 conda-forge protobuf: 3.5.0-py27_0 conda-forge six: 1.11.0-py27_1 conda-forge tensorboard: 0.4.0rc3-py27_0 conda-forge tensorflow: 1.4.0-py27_0 conda-forge webencodings: 0.5-py27_0 conda-forge werkzeug: 0.12.2-py_1 conda-forge Proceed ([y]/n)? y intel-openmp-2 100% |#################################| Time: 0:00:01 478.61 kB/s mkl-2018.0.1-h 100% |#################################| Time: 0:01:08 2.84 MB/s enum34-1.1.6-p 100% |#################################| Time: 0:00:01 32.00 kB/s funcsigs-1.0.2 100% |#################################| Time: 0:00:00 38.56 kB/s futures-3.2.0- 100% |#################################| Time: 0:00:00 74.10 kB/s markdown-2.6.9 100% |#################################| Time: 0:00:01 73.17 kB/s six-1.11.0-py2 100% |#################################| Time: 0:00:00 62.19 kB/s webencodings-0 100% |#################################| Time: 0:00:00 25.65 kB/s werkzeug-0.12. 100% |#################################| Time: 0:00:14 17.24 kB/s html5lib-0.999 100% |#################################| Time: 0:00:04 39.10 kB/s bleach-1.5.0-p 100% |#################################| Time: 0:00:00 66.33 kB/s protobuf-3.5.0 100% |#################################| Time: 0:00:47 128.41 kB/s tensorboard-0. 100% |#################################| Time: 0:00:22 77.40 kB/s pbr-3.1.1-py27 100% |#################################| Time: 0:00:02 41.01 kB/s mock-2.0.0-py2 100% |#################################| Time: 0:00:03 30.23 kB/s tensorflow-1.4 100% |#################################| Time: 0:03:53 153.09 kB/s (tensorflow) deeplearning@deeplearningsinglenode:~$ (tensorflow) deeplearning@deeplearningsinglenode:~$
上面的步驟完成後，從conda環境中退出:
(tensorflow)$ source deactivate
第四步、測試安裝是否成功
首先激活 tensorflow 環境，而後進入 python，最後導入 tensorflow 庫。若是導入成功則代表安裝成功。
(tensorflow) deeplearning@deeplearningsinglenode:~$ source deactivate deeplearning@deeplearningsinglenode:~$ deeplearning@deeplearningsinglenode:~$ deeplearning@deeplearningsinglenode:~$ source activate tensorflow (tensorflow) deeplearning@deeplearningsinglenode:~$ (tensorflow) deeplearning@deeplearningsinglenode:~$ python Python 2.7.14 |Anaconda, Inc.| (default, Nov 20 2017, 18:04:19) [GCC 7.2.0] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf >>> hello = tf.constant('Hi,TensorFlow!') >>> sess = tf.Session() 2017-12-04 19:18:08.790862: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA >>> print sess.run(hello) Hi,TensorFlow! >>>
第五步、須要使用 TensorFlow 的時候必須從新激活
當使用完畢後，關閉 tensorflow 環境。
Use exit() or Ctrl-D (i.e. EOF) to exit >>> exit() (tensorflow) deeplearning@deeplearningsinglenode:~$ (tensorflow) deeplearning@deeplearningsinglenode:~$ (tensorflow) deeplearning@deeplearningsinglenode:~$ (tensorflow) deeplearning@deeplearningsinglenode:~$ source deactivate deeplearning@deeplearningsinglenode:~$
而後你的終端提示符就會變會原的樣子。
當你須要再次使用的時候就必須再次激活 tensorflow 環境。
source activate tensorflow
..........
......
關閉 tensorflow 環境，並從新激活
第五步、 Finally
至此，你已經擁有了一個能夠玩耍機器學習的 tensorflow 環境，好好玩耍吧：）
你能夠參照官方文檔快速的運行一個手寫數字識別的示例。友情提示：僅 CPU 版本你須要有足夠的耐心。。。。。。
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