官术网_书友最值得收藏!

Installing Python

We will be using virtualenv to create an isolated Python virtual environment. While this isn't strictly necessary, it's an excellent practice. By doing so, we will keep all our Python libraries for this project in a separate isolated environment that won't interfere with the system Python installation. Additionally, virtualenv environments will make it easier to package and deploy our deep neural networks later on.

Let's start by installing Python, pip, and virtualenv, using the aptitude package manager in Ubuntu. The following is the code:

sudo apt-get install python3-pip python3-dev python-virtualenv

Now we can create a virtual environment for our work. We will be keeping all our virtual environment files in a folder called ~/deep-learn. You are free to choose any name you wish for this virtual environment. The following code shows how to create a virtual environment:

virtualenv --no-site-packages -p python3 ~/deep-learn
If you're an experienced Python developer, you might have noticed that I've set up the environment to default to Python 3.x. That's most certainly not required, and TensorFlow / Keras both support Python 2.7. That said, the author feels a moral obligation to the Python community to support modern versions of Python.

Now that the virtual environment has been created, you can activate it as follows:

$source ~/deep-learn/bin/activate
(deep-learn)$ # notice the shell changes to indicate the virtualenv
At this point, every time you log in you will need to activate the virtual environment you want to work in. If you would like to always enter the virtual environment you just created, you can add the source command to ~/.bash_profile.

Now that we've configured our virtual environment, we can add Python packages as required within it. To start, let's make sure we have the latest version of pip, the Python package manager:

easy_install -U pip

Lastly, I recommend installing IPython, which is an interactive Python shell that makes development much easier.

pip install ipython

And that's it. Now we're ready to install TensorFlow and Keras.

主站蜘蛛池模板: 阿鲁科尔沁旗| 和顺县| 峨边| 珲春市| 开平市| 陆河县| 青神县| 谷城县| 泰顺县| 格尔木市| 东城区| 易门县| 永川市| 怀宁县| 华宁县| 甘南县| 神农架林区| 泉州市| 五家渠市| 昌宁县| 玉田县| 秦安县| 九江县| 彝良县| 长治县| 焦作市| 大厂| 黄山市| 竹溪县| 雷波县| 房山区| 廊坊市| 大同市| 定州市| 海晏县| 江城| 海阳市| 汝阳县| 芜湖县| 连江县| 淮南市|