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()
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