运用Anaconda对python 3.6与tensorflow-gpu与pip环境配置

柔情只为你懂 2022-03-18 05:38 262阅读 0赞

**背景**：代码是python3版本编写，则运用python2.7运行会报错，运用python3版本运行又显示没有安装tensorflow。所以运用python3版配置与安装tensorflow。

**目的**：运用anaconda来进行python3.6安装与配置tensorflow

**目录**

一、问题描述

二、旧版本解决方法（无用可不看）

2.1 安装python3

2.2 升级旧pip

2.3 为python3安装pip3

三、配置环境

3.1 安装anaconda

3.2 创建环境

3.3 激活环境

3.4 配置tensorflow-gpu

3.5 更新pip

--------------------

# 一、问题描述 #

运用python运行程序时，python3的程序，运用python2运行就会报错。

jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ python dataset_tool_tf.py --input-dir datasets/part_BSDS300/images/train --out=datasets/part_bsd300.tfrecords
    Loading image list from datasets/part_BSDS300/images/train
    Traceback (most recent call last):
      File "dataset_tool_tf.py", line 94, in <module>
        main()
      File "dataset_tool_tf.py", line 70, in main
        os.makedirs(outdir, exist_ok=True)
    TypeError: makedirs() got an unexpected keyword argument 'exist_ok'

出现此错误，原来作者要求版本为python 3.6 ，这样报错的版本为python 2.7.6

jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ python
    Python 2.7.6 (default, Oct 26 2016, 20:30:19)
    [GCC 4.8.4] on linux2
    Type "help", "copyright", "credits" or "license" for more information.
    >>> quit()

python3的版本输入的时候，报错为tensorflow配置不对。

jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ python3 dataset_tool_tf.py --input-dir datasets/part_BSDS300/images/train --out=datasets/part_bsd300.tfrecords
    Traceback (most recent call last):
      File "dataset_tool_tf.py", line 12, in <module>
        import tensorflow as tf
    ImportError: No module named 'tensorflow'
    jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ python3
    Python 3.5.2 (default, May 23 2017, 10:15:40)
    [GCC 5.4.1 20160904] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> quit()

# 二、旧版本解决方法（无用可不看） #

## 2.1 安装python3 ##

输入python3，如果没有出现以下信息表示python3没有安装

jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ python3
    Python 3.5.2 (default, May 23 2017, 10:15:40)
    [GCC 5.4.1 20160904] on linux
    Type "help", "copyright", "credits" or "license" for more information.

先到官方网站下载python3的安装包

https://www.python.org/downloads/source/  －－－例如Python-3.5.2.tar.xz

上传包到服务器

解压 tar -xf Python-3.5.2.tar.xz

编译安装

**！！！！注意 注意** ⚠️  在编译之前需要安装一些必须的依赖，否则当报错的时候还得重新编译

安装必要依赖（至少需要如下两个）

yum install openssl-devel   -y
    yum install zlib-devel  -y

好了现在可以安心的编译咯：

cd Python-3.5.2
    ./configure --prefix=/opt/Python     #安装目录可以自己定义无所谓。
    make
    make install

编译完成后会在如 /opt/下生成Python的文件夹 ，没错这就是编译完成的python  －－为了方便之行小伙伴们可以自己定义一个软连接如下：

# ln -s /opt/Python/bin/python3 /usr/bin/python3

这样就可以直接使用python3了。

## 2.2 升级旧pip ##

升级旧版本pip，

sudo pip install --upgrade pip

Installing collected packages: pip
      Found existing installation: pip 18.0
        Uninstalling pip-18.0:
          Successfully uninstalled pip-18.0
    Successfully installed pip-19.0.2

此时pip2被升级为19.0.2

## 2.3 为python3安装pip3 ##

输入pip3，下面信息反映出pip3没有安装

jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ pip3
    程序“pip3”尚未安装。 您可以使用以下命令安装：
    sudo apt-get install python3-pip
    您必须启用universe 组件

输入sudo apt-get install python3-pip之后依然出现相应的报错

jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ sudo apt-get install python3-pip
    [sudo] password for jcx:
    正在读取软件包列表... 完成
    正在分析软件包的依赖关系树
    正在读取状态信息... 完成
    python3-pip 已经是最新的版本。
    下列软件包是自动安装的并且现在不需要了：
      libasound2:i386 libexpat1:i386 libfontconfig1:i386 libfreetype6:i386
      libice6:i386 libjpeg62:i386 libntdb1 libsm6:i386 libx11-6:i386 libxau6:i386
      libxcb1:i386 libxdamage1:i386 libxdmcp6:i386 libxext6:i386 libxfixes3:i386
      libxinerama1:i386 libxrandr2:i386 libxrender1:i386 libxtst6:i386 python-ntdb
    Use 'apt-get autoremove' to remove them.
    升级了 0 个软件包，新安装了 0 个软件包，要卸载 0 个软件包，有 406 个软件包未被升级。
    jcx@smart-dsp:~/Desktop/xxr2019/NVlabs_noise2noise$ pip3
    程序“pip3”尚未安装。 您可以使用以下命令安装：
    sudo apt-get install python3-pip
    您必须启用universe 组件

解决方案见其他人帖子，我们放弃这种方案，运用anaconda来配置相应的环境

# 三、配置环境 #

为了更好的进行版本管理及不同环境下的管理，我们安装anaconda来进行相应的版本管理。

## 3.1 安装anaconda ##

[https://blog.csdn.net/weixin\_36474809/article/details/87804903][https_blog.csdn.net_weixin_36474809_article_details_87804903]

## 3.2 创建环境 ##

创建相应的环境

conda create -n n2n python=3.6

激活及取消相应的环境运用下面命令行。

# To activate this environment, use:
    # > source activate n2n
    #
    # To deactivate an active environment, use:
    # > source deactivate
    #

## 3.3 激活环境 ##

注意，旧版本输入conda activate n2n，

出现下面错误结果

jcx@smart-dsp:~/Desktop/xxr2019/anaconda$ conda activate n2n
    
    CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
    If your shell is Bash or a Bourne variant, enable conda for the current user with
    
        $ echo ". /home/jcx/anaconda3/etc/profile.d/conda.sh" >> ~/.bashrc
    
    or, for all users, enable conda with
    
        $ sudo ln -s /home/jcx/anaconda3/etc/profile.d/conda.sh /etc/profile.d/conda.sh
    
    The options above will permanently enable the 'conda' command, but they do NOT
    put conda's base (root) environment on PATH.  To do so, run
    
        $ conda activate
    
    in your terminal, or to put the base environment on PATH permanently, run
    
        $ echo "conda activate" >> ~/.bashrc
    
    Previous to conda 4.4, the recommended way to activate conda was to modify PATH in
    your ~/.bashrc file.  You should manually remove the line that looks like
    
        export PATH="/home/jcx/anaconda3/bin:$PATH"
    
    ^^^ The above line should NO LONGER be in your ~/.bashrc file! ^^^

需要输入新的指令 source activate n2n

jcx@smart-dsp:~/Desktop/xxr2019/anaconda$ source activate n2n
    (n2n) jcx@smart-dsp:~/Desktop/xxr2019/anaconda$

## 3.4 配置tensorflow-gpu ##

上一步若完成失败，则输入下面会出现报错conda install tensorflow-gpu

jcx@smart-dsp:~/Desktop/xxr2019/anaconda$ conda install tensorflow-gpu
    Solving environment: failed
    
    UnsatisfiableError: The following specifications were found to be in conflict:
      - tensorflow-gpu
    Use "conda info <package>" to see the dependencies for each package.

若是上一步运行正确，则会安装相应tf，我们安装的tf信息如下：

The following NEW packages will be INSTALLED:
    
        _tflow_select:       2.1.0-gpu
        absl-py:             0.7.0-py36_0
        astor:               0.7.1-py36_0
        blas:                1.0-mkl
        c-ares:              1.15.0-h7b6447c_1
        cudatoolkit:         9.2-0
        cudnn:               7.3.1-cuda9.2_0
        cupti:               9.2.148-0
        gast:                0.2.2-py36_0
        grpcio:              1.16.1-py36hf8bcb03_1
        h5py:                2.9.0-py36h7918eee_0
        hdf5:                1.10.4-hb1b8bf9_0
        intel-openmp:        2019.1-144
        keras-applications:  1.0.6-py36_0
        keras-preprocessing: 1.0.5-py36_0
        libgfortran-ng:      7.3.0-hdf63c60_0
        libprotobuf:         3.6.1-hd408876_0
        markdown:            3.0.1-py36_0
        mkl:                 2019.1-144
        mkl_fft:             1.0.10-py36ha843d7b_0
        mkl_random:          1.0.2-py36hd81dba3_0
        numpy:               1.15.4-py36h7e9f1db_0
        numpy-base:          1.15.4-py36hde5b4d6_0
        protobuf:            3.6.1-py36he6710b0_0
        scipy:               1.2.0-py36h7c811a0_0
        six:                 1.12.0-py36_0
        tensorboard:         1.12.2-py36he6710b0_0
        tensorflow:          1.12.0-gpu_py36he74679b_0
        tensorflow-base:     1.12.0-gpu_py36had579c0_0
        tensorflow-gpu:      1.12.0-h0d30ee6_0
        termcolor:           1.1.0-py36_1
        werkzeug:            0.14.1-py36_0

最终输出如下信息，表明安装完成。

Preparing transaction: done
    Verifying transaction: done
    Executing transaction: done

## 3.5 更新pip ##

(n2n) jcx@smart-dsp:~/Desktop/xxr2019/anaconda$ python -m pip install --upgrade pip
    Collecting pip
      Using cached https://files.pythonhosted.org/packages/d7/41/34dd96bd33958e52cb4da2f1bf0818e396514fd4f4725a79199564cd0c20/pip-19.0.2-py2.py3-none-any.whl
    Installing collected packages: pip
      Found existing installation: pip 19.0.1
        Uninstalling pip-19.0.1:
          Successfully uninstalled pip-19.0.1
    Successfully installed pip-19.0.2

[https_blog.csdn.net_weixin_36474809_article_details_87804903]: https://blog.csdn.net/weixin_36474809/article/details/87804903