代码改变世界
[登录 · 注册]
  • 全网最详细的基于Ubuntu14.04/16.04 + Anaconda2 / Anaconda3 + Python2.7/3.4/3.5/3.6安装Tensorflow详细步骤(图文)(博主推荐)
  •   不多说,直接上干货!

    前言

      建议参照最新的tensorflow安装步骤(Linux,官方网站经常访问不是很稳定,所以给了一个github的地址):          https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/install/install_linux.md

      最近,tensorflow网站上给出了新的使用Anaconda配置和安装Tensorflow的步骤,经过测试,在国内可以无障碍的访问。Anaconda 是一个基于python的科学计算包集合,目前支持Python 2.7,3.4,3.5,3.6。

      注意:在安装过程中如果出现很长的报错,观察错误信息的末尾,如果是网络链接相关,就重新运行一遍语句即可(如出现进度条不动的情况,也可重新运行语句),Anaconda自身约500M,tensorflow所需软件包约几十M。

      操作系统: Ubuntu 14.04   或  Ubuntu16.04

      这是Github官网给出的安装步骤

    https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/install/install_linux.md

     

     

     

     

    第一步、 安装Anaconda

      从anaconda官网(https://www.continuum.io/downloads)上下载linux版本的安装文件,运行完成安装。

      我这里是以Anaconda2-5.0.1-Linux-x86_64.sh为例,Anaconda3一样啦。这个很简单。

     

    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. Continuum reserves the right to change which third party tools are provided in Anaconda.
    
    In particular, Anaconda contains re-distributable, run-time, shared-library files from the Intel(TM) Math Kernel Library ("MKL bina
    ries"). You are specifically authorized to use the MKL binaries with your installation of Anaconda. You are also authorized to redi
    stribute the MKL binaries with Anaconda or in the conda package that contains them. Use and redistribution of the MKL binaries are 
    subject to the licensing terms located at https://software.intel.com/en-us/license/intel-simplified-software-license. If needed, in
    structions for removing the MKL binaries after installation of Anaconda are available at http://www.anaconda.com.
    
    Anaconda also contains cuDNN software binaries from NVIDIA Corporation ("cuDNN binaries"). You are specifically authorized to use t
    he cuDNN binaries with your installation of Anaconda. You are also authorized to redistribute the cuDNN binaries with an Anaconda p
    ackage that contains them. If needed, instructions for removing the cuDNN binaries after installation of Anaconda are available at 
    http://www.anaconda.com.
    
    
    Cryptography Notice
    ===================
    
    This distribution includes cryptographic software. The country in which you currently reside may have restrictions on the import, p
    ossession, use, and/or re-export to another country, of encryption software. BEFORE using any encryption software, please check you
    r country's laws, regulations and policies concerning the import, possession, or use, and re-export of encryption software, to see 
    if this is permitted. See the Wassenaar Arrangement <http://www.wassenaar.org/> for more information.
    
    Continuum has self-classified this software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information securit
    y software using or performing cryptographic functions with asymmetric algorithms. The form and manner of this distribution makes i
    t eligible for export under the License Exception ENC Technology Software Unrestricted (TSU) exception (see the BIS Export Administ
    ration Regulations, Section 740.13) for both object code and source code. In addition, the Intel(TM) Math Kernel Library contained 
    in Continuum's software is classified by Intel(TM) as ECCN 5D992b with no license required for export to non-embargoed countries.
    
    The following packages are included in this distribution that relate to cryptography:
    
    openssl
        The OpenSSL Project is a collaborative effort to develop a robust, commercial-grade, full-featured, and Open Source toolkit imp
    lementing the Transport Layer Security (TLS) and Secure Sockets Layer (SSL) protocols as well as a full-strength general purpose cr
    yptography library.
    
    pycrypto
        A collection of both secure hash functions (such as SHA256 and RIPEMD160), and various encryption algorithms (AES, DES, RSA, El
    Gamal, etc.).
    
    pyopenssl
        A thin Python wrapper around (a subset of) the OpenSSL library.
    
    kerberos (krb5, non-Windows platforms)
        A network authentication protocol designed to provide strong authentication for client/server applications by using secret-key 
    cryptography.
    
    cryptography
        A Python library which exposes cryptographic recipes and primitives.

     

    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

    installing: python-2.7.14-hc2b0042_21 ...
    Python 2.7.14 :: Anaconda, Inc.
    installing: ca-certificates-2017.08.26-h1d4fec5_0 ...
    installing: conda-env-2.6.0-h36134e3_1 ...
    installing: intel-openmp-2018.0.0-h15fc484_7 ...
    installing: libgcc-ng-7.2.0-h7cc24e2_2 ...
    installing: libgfortran-ng-7.2.0-h9f7466a_2 ...
    installing: libstdcxx-ng-7.2.0-h7a57d05_2 ...
    installing: bzip2-1.0.6-h0376d23_1 ...
    installing: expat-2.2.4-hc00ebd1_1 ...
    installing: gmp-6.1.2-hb3b607b_0 ...
    installing: graphite2-1.3.10-hc526e54_0 ...
    installing: icu-58.2-h211956c_0 ...
    installing: jbig-2.1-hdba287a_0 ...
    installing: jpeg-9b-habf39ab_1 ...
    installing: libffi-3.2.1-h4deb6c0_3 ...
    installing: libsodium-1.0.13-h31c71d8_2 ...
    installing: libssh2-1.8.0-h8c220ad_2 ...
    installing: libtool-2.4.6-hd50d1a6_0 ...
    installing: libxcb-1.12-h84ff03f_3 ...
    installing: lzo-2.10-h1bfc0ba_1 ...
    installing: mkl-2018.0.0-hb491cac_4 ...
    installing: ncurses-6.0-h06874d7_1 ...
    installing: openssl-1.0.2l-h077ae2c_5 ...
    installing: patchelf-0.9-hf79760b_2 ...
    installing: pcre-8.41-hc71a17e_0 ...
    installing: pixman-0.34.0-h83dc358_2 ...
    installing: tk-8.6.7-h5979e9b_1 ...
    installing: unixodbc-2.3.4-hc36303a_1 ...
    installing: xz-5.2.3-h2bcbf08_1 ...
    installing: yaml-0.1.7-h96e3832_1 ...
    installing: zlib-1.2.11-hfbfcf68_1 ...
    installing: curl-7.55.1-hcb0b314_2 ...
    installing: glib-2.53.6-hc861d11_1 ...
    installing: hdf5-1.10.1-hb0523eb_0 ...
    installing: libedit-3.1-heed3624_0 ...
    installing: libpng-1.6.32-hda9c8bc_2 ...
    installing: libtiff-4.0.8-h90200ff_9 ...
    installing: libxml2-2.9.4-h6b072ca_5 ...
    installing: mpfr-3.1.5-h12ff648_1 ...
    installing: pandoc-1.19.2.1-hea2e7c5_1 ...
    installing: readline-7.0-hac23ff0_3 ...
    installing: zeromq-4.2.2-hb0b69da_1 ...
    installing: dbus-1.10.22-h3b5a359_0 ...
    installing: freetype-2.8-h52ed37b_0 ...
    installing: gstreamer-1.12.2-h4f93127_0 ...
    installing: libxslt-1.1.29-hcf9102b_5 ...
    installing: mpc-1.0.3-hf803216_4 ...
    installing: sqlite-3.20.1-h6d8b0f3_1 ...
    installing: fontconfig-2.12.4-h88586e7_1 ...
    installing: gst-plugins-base-1.12.2-he3457e5_0 ...
    installing: alabaster-0.7.10-py27he5a193a_0 ...
    installing: asn1crypto-0.22.0-py27h94ebe91_1 ...
    installing: backports-1.0-py27h63c9359_1 ...
    installing: backports_abc-0.5-py27h7b3c97b_0 ...
    installing: beautifulsoup4-4.6.0-py27h3f86ba9_1 ...
    installing: bitarray-0.8.1-py27h304d4c6_0 ...
    installing: boto-2.48.0-py27h9556ac2_1 ...
    installing: cairo-1.14.10-haa5651f_5 ...
    installing: cdecimal-2.3-py27h4e63abe_1 ...
    installing: certifi-2017.7.27.1-py27h9ceb091_0 ...
    installing: chardet-3.0.4-py27hfa10054_1 ...
    installing: click-6.7-py27h4225b90_0 ...
    installing: cloudpickle-0.4.0-py27ha64365b_0 ...
    installing: colorama-0.3.9-py27h5cde069_0 ...
    installing: configparser-3.5.0-py27h5117587_0 ...
    installing: contextlib2-0.5.5-py27hbf4c468_0 ...
    installing: dask-core-0.15.3-py27h53a7ee6_0 ...
    installing: decorator-4.1.2-py27h1544723_0 ...
    installing: docutils-0.14-py27hae222c1_0 ...
    installing: enum34-1.1.6-py27h99a27e9_1 ...
    installing: et_xmlfile-1.0.1-py27h75840f5_0 ...
    installing: fastcache-1.0.2-py27h4cb8e01_0 ...
    installing: filelock-2.0.12-py27h38fa839_0 ...
    installing: funcsigs-1.0.2-py27h83f16ab_0 ...
    installing: functools32-3.2.3.2-py27h4ead58f_1 ...
    installing: futures-3.1.1-py27hdbc8cbb_0 ...
    installing: glob2-0.5-py27hd3b7d1f_1 ...
    installing: gmpy2-2.0.8-py27hc856308_1 ...
    installing: greenlet-0.4.12-py27hac09c53_0 ...
    installing: grin-1.2.1-py27h54abee7_1 ...
    installing: heapdict-1.0.0-py27h33770af_0 ...
    installing: idna-2.6-py27h5722d68_1 ...
    installing: imagesize-0.7.1-py27hd17bf80_0 ...
    installing: ipaddress-1.0.18-py27h337fd85_0 ...
    installing: ipython_genutils-0.2.0-py27h89fb69b_0 ...
    installing: itsdangerous-0.24-py27hb8295c1_1 ...
    installing: jdcal-1.3-py27h2cc5433_0 ...
    installing: jedi-0.10.2-py27h8af4e35_0 ...
    installing: lazy-object-proxy-1.3.1-py27h682c727_0 ...
    installing: locket-0.2.0-py27h73929a2_1 ...
    installing: lxml-4.1.0-py27hb025457_0 ...
    installing: markupsafe-1.0-py27h97b2822_1 ...
    installing: mccabe-0.6.1-py27h0e7c7be_1 ...
    installing: mistune-0.7.4-py27h6da7e90_0 ...
    installing: mkl-service-1.1.2-py27hb2d42c5_4 ...
    installing: mpmath-0.19-py27h4bb41bd_2 ...
    installing: msgpack-python-0.4.8-py27hc2fa789_0 ...
    installing: multipledispatch-0.4.9-py27h9b5f95a_0 ...
    installing: numpy-1.13.3-py27hbcc08e0_0 ...
    installing: olefile-0.44-py27h4bd3e3c_0 ...
    installing: pandocfilters-1.4.2-py27h428e1e5_1 ...
    installing: path.py-10.3.1-py27hc258cac_0 ...
    installing: pep8-1.7.0-py27h444351c_0 ...
    installing: pkginfo-1.4.1-py27hee1a9ad_1 ...
    installing: ply-3.10-py27hd6d9ae5_0 ...
    installing: psutil-5.4.0-py27h7da3062_0 ...
    installing: ptyprocess-0.5.2-py27h4ccb14c_0 ...
    installing: py-1.4.34-py27he5894e4_1 ...
    installing: pycodestyle-2.3.1-py27h904819d_0 ...
    installing: pycosat-0.6.2-py27h1cf261c_1 ...
    installing: pycparser-2.18-py27hefa08c5_1 ...
    installing: pycrypto-2.6.1-py27h9abbf5c_1 ...
    installing: pycurl-7.43.0-py27hcf8ebea_3 ...
    installing: pyodbc-4.0.17-py27h7f7627d_0 ...
    installing: pyparsing-2.2.0-py27hf1513f8_1 ...
    installing: pysocks-1.6.7-py27he2db6d2_1 ...
    installing: pytz-2017.2-py27hcac29fa_1 ...
    installing: pyyaml-3.12-py27h2d70dd7_1 ...
    installing: pyzmq-16.0.2-py27h297844f_2 ...
    installing: qt-5.6.2-h974d657_12 ...
    installing: qtpy-1.3.1-py27h63d3751_0 ...
    installing: rope-0.10.5-py27hcb0a616_0 ...
    installing: ruamel_yaml-0.11.14-py27h672d447_2 ...
    installing: scandir-1.6-py27hf7388dc_0 ...
    installing: simplegeneric-0.8.1-py27h19e43cd_0 ...
    installing: sip-4.18.1-py27he9ba0ab_2 ...
    installing: six-1.11.0-py27h5f960f1_1 ...
    installing: snowballstemmer-1.2.1-py27h44e2768_0 ...
    installing: sortedcontainers-1.5.7-py27he59936f_0 ...
    installing: sphinxcontrib-1.0-py27h1512b58_1 ...
    installing: sqlalchemy-1.1.13-py27hb0a01da_0 ...
    installing: subprocess32-3.2.7-py27h373dbce_0 ...
    installing: tblib-1.3.2-py27h51fe5ba_0 ...
    installing: toolz-0.8.2-py27hd3b1e7e_0 ...
    installing: typing-3.6.2-py27h66f49e2_0 ...
    installing: unicodecsv-0.14.1-py27h5062da9_0 ...
    installing: wcwidth-0.1.7-py27h9e3e1ab_0 ...
    installing: webencodings-0.5.1-py27hff10b21_1 ...
    installing: werkzeug-0.12.2-py27hbf75dff_0 ...
    installing: wrapt-1.10.11-py27h04f6869_0 ...
    installing: xlrd-1.1.0-py27ha77178f_1 ...
    installing: xlsxwriter-1.0.2-py27h12cbc6b_0 ...
    installing: xlwt-1.3.0-py27h3d85d97_0 ...
    installing: babel-2.5.0-py27h20693cd_0 ...
    installing: backports.shutil_get_terminal_size-1.0.0-py27h5bc021e_2 ...
    installing: bottleneck-1.2.1-py27h21b16a3_0 ...
    installing: cffi-1.10.0-py27hf1aaaf4_1 ...
    installing: conda-verify-2.0.0-py27hf052a9d_0 ...
    installing: cycler-0.10.0-py27hc7354d3_0 ...
    installing: cytoolz-0.8.2-py27hf14aec9_0 ...
    installing: entrypoints-0.2.3-py27h502b47d_2 ...
    installing: h5py-2.7.0-py27h71d1790_1 ...
    installing: harfbuzz-1.5.0-h2545bd6_0 ...
    installing: html5lib-0.999999999-py27hdf15f34_0 ...
    installing: llvmlite-0.20.0-py27_0 ...
    installing: networkx-2.0-py27hfc23926_0 ...
    installing: nltk-3.2.4-py27h41293c3_0 ...
    installing: numexpr-2.6.2-py27he5efce1_1 ...
    installing: openpyxl-2.4.8-py27h9f0c937_1 ...
    installing: packaging-16.8-py27h5e07c7c_1 ...
    installing: partd-0.3.8-py27h4e55004_0 ...
    installing: pathlib2-2.3.0-py27h6e9d198_0 ...
    installing: pexpect-4.2.1-py27hcf82287_0 ...
    installing: pillow-4.2.1-py27h7cd2321_0 ...
    installing: pycairo-1.13.3-py27hea6d626_0 ...
    installing: pyqt-5.6.0-py27h4b1e83c_5 ...
    installing: python-dateutil-2.6.1-py27h4ca5741_1 ...
    installing: pywavelets-0.5.2-py27hecda097_0 ...
    installing: qtawesome-0.4.4-py27hd7914c3_0 ...
    installing: scipy-0.19.1-py27h1edc525_3 ...
    installing: setuptools-36.5.0-py27h68b189e_0 ...
    installing: singledispatch-3.4.0.3-py27h9bcb476_0 ...
    installing: sortedcollections-0.5.3-py27h135218e_0 ...
    installing: sphinxcontrib-websupport-1.0.1-py27hf906f22_1 ...
    installing: ssl_match_hostname-3.5.0.1-py27h4ec10b9_2 ...
    installing: sympy-1.1.1-py27hc28188a_0 ...
    installing: traitlets-4.3.2-py27hd6ce930_0 ...
    installing: zict-0.1.3-py27h12c336c_0 ...
    installing: backports.functools_lru_cache-1.4-py27he8db605_1 ...
    installing: bleach-2.0.0-py27h3a0dcc8_0 ...
    installing: clyent-1.2.2-py27h7276e6c_1 ...
    installing: cryptography-2.0.3-py27hea39389_1 ...
    installing: cython-0.26.1-py27hdbcff32_0 ...
    installing: datashape-0.5.4-py27hf507385_0 ...
    installing: get_terminal_size-1.0.0-haa9412d_0 ...
    installing: gevent-1.2.2-py27h475ea6a_0 ...
    installing: imageio-2.2.0-py27hf108a7f_0 ...
    installing: isort-4.2.15-py27hcfa4749_0 ...
    installing: jinja2-2.9.6-py27h82327ae_1 ...
    installing: jsonschema-2.6.0-py27h7ed5aa4_0 ...
    installing: jupyter_core-4.3.0-py27hcd9ae3a_0 ...
    installing: navigator-updater-0.1.0-py27h0f9cd39_0 ...
    installing: nose-1.3.7-py27heec2199_2 ...
    installing: numba-0.35.0-np113py27_10 ...
    installing: pandas-0.20.3-py27h820b67f_2 ...
    installing: pango-1.40.11-h8191d47_0 ...
    installing: patsy-0.4.1-py27hd1cf8c0_0 ...
    installing: pickleshare-0.7.4-py27h09770e1_0 ...
    installing: pyflakes-1.6.0-py27h904a57d_0 ...
    installing: pygments-2.2.0-py27h4a8b6f5_0 ...
    installing: pytables-3.4.2-py27h1f7bffc_2 ...
    installing: pytest-3.2.1-py27h98000ae_1 ...
    installing: scikit-learn-0.19.1-py27h445a80a_0 ...
    installing: testpath-0.3.1-py27hc38d2c4_0 ...
    installing: tornado-4.5.2-py27h97b179f_0 ...
    installing: wheel-0.29.0-py27h411dd7b_1 ...
    installing: astroid-1.5.3-py27h8f8f47c_0 ...
    installing: astropy-2.0.2-py27h57072c0_4 ...
    installing: bkcharts-0.2-py27h241ae91_0 ...
    installing: bokeh-0.12.10-py27he46cc6b_0 ...
    installing: distributed-1.19.1-py27h38c4a05_0 ...
    installing: flask-0.12.2-py27h6d5c1cd_0 ...
    installing: jupyter_client-5.1.0-py27hbee1118_0 ...
    installing: matplotlib-2.1.0-py27h09aba24_0 ...
    installing: nbformat-4.4.0-py27hed7f2b2_0 ...
    installing: pip-9.0.1-py27hbf658b2_3 ...
    installing: prompt_toolkit-1.0.15-py27h1b593e1_0 ...
    installing: pyopenssl-17.2.0-py27h189ff3b_0 ...
    installing: statsmodels-0.8.0-py27hc87d62d_0 ...
    installing: terminado-0.6-py27h4be8df9_0 ...
    installing: dask-0.15.3-py27hb94b45f_0 ...
    installing: flask-cors-3.0.3-py27h1a8a27f_0 ...
    installing: ipython-5.4.1-py27h36c99b6_1 ...
    installing: nbconvert-5.3.1-py27he041f76_0 ...
    installing: pylint-1.7.4-py27h6bc7935_0 ...
    installing: seaborn-0.8.0-py27h9d2aaa1_0 ...
    installing: urllib3-1.22-py27ha55213b_0 ...
    installing: ipykernel-4.6.1-py27hc93e584_0 ...
    installing: odo-0.5.1-py27h9170de3_0 ...
    installing: requests-2.18.4-py27hc5b0589_1 ...
    installing: scikit-image-0.13.0-py27h06cb35d_1 ...
    installing: anaconda-client-1.6.5-py27hc8169bf_0 ...
    installing: blaze-0.11.3-py27h5f341da_0 ...
    installing: conda-4.3.30-py27h6ae6dc7_0 ...
    installing: jupyter_console-5.2.0-py27hc6bee7e_1 ...
    installing: notebook-5.0.0-py27h3661c2b_2 ...
    installing: qtconsole-4.3.1-py27hc444b0d_0 ...
    installing: sphinx-1.6.3-py27hf9b1778_0 ...
    installing: anaconda-project-0.8.0-py27hd7a9a97_0 ...
    installing: conda-build-3.0.27-py27hff9f855_0 ...
    installing: jupyterlab_launcher-0.4.0-py27h0e16d15_0 ...
    installing: numpydoc-0.7.0-py27h9647a75_0 ...
    installing: widgetsnbextension-3.0.2-py27hcb77dec_1 ...
    installing: anaconda-navigator-1.6.9-py27hfbc306d_0 ...
    installing: ipywidgets-7.0.0-py27h4fda95d_0 ...
    installing: jupyterlab-0.27.0-py27h42ebfef_2 ...
    installing: spyder-3.2.4-py27h04a3490_0 ...
    installing: _ipyw_jlab_nb_ext_conf-0.1.0-py27h08a7f0c_0 ...
    installing: jupyter-1.0.0-py27h505fd4b_0 ...
    installing: anaconda-5.0.1-py27hd9359a7_1 ...
    installation finished.
    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!

       因为这是一个坑,是安装时最后一步添加环境变量的时候没有选择yes导致运行 conda info 时出错,很好解决,根据错误提示:

      然后,紧接着去配置Anaconda2的环境变量。怎么做呢?很简单。

      在命令行输入就可以了。

    $ export PATH=/home/deeplearning/anaconda2/bin:$PATH

    第二步、建立一个tensorflow的运行环境

    # Python 2.7 (选好自己的) 
    $ conda create -n tensorflow python=2.7  
      
    # Python 3.4  (选好自己的)
    $ conda create -n tensorflow python=3.4  
      
    # Python 3.5  (选好自己的)
    $ conda create -n tensorflow python=3.5  

       注意:在这一步,你也许会遇到conda: command not found

     

      遇到这个问题的时候, 


      解决方法是:

    export PATH="/home/[your_name]/anaconda/bin:$PATH"

      比如我这里是

    export PATH=/home/deeplearning/anaconda2/bin:$PATH

      但是下一次重启之后,还是会出现这个问题,所以我们要激活下 ~/.bash_profile

    . ~/.bash_profile
    #或者
    source ~/.bash_profile
    或者source /etc/profile

     那是因为我的环境变量是如下:

     

    #Anaconda2
    ANACONDA2_HOME=/home/deeplearning/anaconda2
    ANACONDA2_BIN=/home/deeplearning/anaconda2/bin
    PATH=$PATH:$ANACONDA2_BIN
    export ANACONDA2_HOME ANACONDA2_BIN PATH

       所以,

    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环境中安装tensorflow

      在conda环境中安装tensorflow的好处是可以便捷的管理tensorflow的依赖包。

      分为两个步骤:激活上一步建立的名为tensorflow的conda环境;用conda或者pip工具安装Tensorflow,我选择的是pip方式。

    3.1 pip方式(可以这种方式来安装)

      pip方式需要首先激活conda环境

    deeplearning@deeplearningsinglenode:~$ source activate tensorflow
    (tensorflow) deeplearning@deeplearningsinglenode:~$ 

       然后根据要安装的不同tensorflow版本选择对应的一条环境变量设置export语句(操作系统,Python版本,CPU版本还是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  

     

     

     

      最后根据是python 2还是3版本选择一句进行安装。

    # 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:这是在安装tensorflow的时候创建tensorflow环境失败,这是个坑,因为有些版本地址失效了。

                      换其他版本试试。比如如下我现在是2017年12月份,采用conda方式安装tensorflow,版本已经是1.4.0-py27_0

     

     
     
     
     
     
     
     
     
     

    3.2 conda方式(或者也可以这种方式来安装)

      conda上面目前有人已经做好了tensorflow的pkg,但是版本不一定最新,且只有CPU版本,不支持GPU。

      步骤也是首先激活conda环境,然后调用conda install 语句安装.

    $ 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:~$ 

      上面的步骤完成后,从conda环境中退出:

    (tensorflow)$ source deactivate  
     
     
     
     
     

    第四步、测试安装是否成功

       首先激活 tensorflow 环境,然后进入 python,最后导入 tensorflow 库。如果导入成功则表明安装成功。

    (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、需要使用 TensorFlow 的时候必须重新激活

      当使用完毕后,关闭 tensorflow 环境。

    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:~$ 

      然后你的终端提示符就会变会原的样子。

      当你需要再次使用的时候就必须再次激活 tensorflow 环境。

    source activate tensorflow

      ..........

      ......

      关闭 tensorflow 环境,并重新激活

    第五步、 Finally

      至此,你已经拥有了一个可以玩耍机器学习的 tensorflow 环境,好好玩耍吧:)

      你可以参照官方文档快速的运行一个手写数字识别的示例。友情提示:仅 CPU 版本你需要有足够的耐心。。。。。。

     

     

    欢迎大家,加入我的微信公众号:大数据躺过的坑        人工智能躺过的坑
     
     
     

    同时,大家可以关注我的个人博客

       http://www.cnblogs.com/zlslch/   和     http://www.cnblogs.com/lchzls/      http://www.cnblogs.com/sunnyDream/   

       详情请见:http://www.cnblogs.com/zlslch/p/7473861.html

      人生苦短,我愿分享。本公众号将秉持活到老学到老学习无休止的交流分享开源精神,汇聚于互联网和个人学习工作的精华干货知识,一切来于互联网,反馈回互联网。
      目前研究领域:大数据、机器学习、深度学习、人工智能、数据挖掘、数据分析。 语言涉及:Java、Scala、Python、Shell、Linux等 。同时还涉及平常所使用的手机、电脑和互联网上的使用技巧、问题和实用软件。 只要你一直关注和呆在群里,每天必须有收获

          对应本平台的讨论和答疑QQ群:大数据和人工智能躺过的坑(总群)(161156071) 

     

  • 上一篇:五款实用免费的Python机器学习集成开发环境(5 free Python IDE for Machine Learning)(图文详解)
    下一篇:如何正确且高效实现OSSIM中文化的解决方案(图文详解)
  • 【推广】 阿里云小站-上云优惠聚集地(新老客户同享)更有每天限时秒杀!
    【推广】 云服务器低至0.95折 1核2G ECS云服务器8.1元/月
    【推广】 阿里云老用户升级四重礼遇享6.5折限时折扣!
  • 原文:https://www.cnblogs.com/zlslch/p/7975791.html
走看看 - 开发者的网上家园