昨天试了用Docker跑NLP的Demo，挺顺利，不过今天在学习TF的时候遇到点问题，依然需要一个本地环境来调试。

Step 1 安装Anaconda3

我本地早已经安装好了，在此不重复说了，需要的同学去官网下载安装。

Step 2 使用Conda创建tensorflow环境

conda create -n tensorflow pip python=3.6
source activate tensorflow

更新pip环境

pip install --upgrade pip

Step 3 安装TensorFlow包

pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.12.0-py3-none-any.whl

此处我翻墙了😜

Step 4 测试下

(tensorflow) Joshuas-iMac-Pro:~ joshua$ python
Python 3.6.8 |Anaconda, Inc.| (default, Dec 29 2018, 19:04:46) 
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
'1.12.0'
>>> exit()

Step 5 退出环境

source deactivate

Step 6 练习

创建一个新环境

source activate cnn-text-classification-tf

自己也写了一段练习作业

import tensorflow as tf


def basic_operation():
    v1 = tf.Variable(10)
    v2 = tf.Variable(5)
    addv = v1 + v2
    print(addv)
    print(type(addv))

    c1 = tf.constant(10)
    c2 = tf.constant(5)
    addc = c1 + c2

    print(addc)
    print(type(addc))
    print(type(c1))

    sess = tf.Session()
    tf.global_variables_initializer().run(session=sess)

    print(addv.eval(session=sess))
    print(sess.run(addv))

    graph = tf.Graph()
    with graph.as_default():
        value1 = tf.constant([1, 2])
        value2 = tf.Variable([3, 4])
        mul = value1 * value2

    with tf.Session(graph=graph) as mySession:
        tf.global_variables_initializer().run()
        print('乘法(value1, value2) = ', mySession.run(mul))
        print('乘法(value1, value2) = ', mul.eval())


if __name__ == '__main__':
    basic_operation()