1. 程式人生 > >Docker學習筆記(六)-fixbug3-docker安裝Tensorflow的問題

Docker學習筆記(六)-fixbug3-docker安裝Tensorflow的問題

docker安裝 Tensorflow遇到問題i/o timeout.

docker: Error response from daemon: Get https://gcr.io/v1/_ping: dial tcp 64.233.188.82:443: i/o timeout.

Tensorflow 是Google的一個開源機器學習框架,中國大陸的使用者在使用的時候往往需要爬過GFW牆,藉助VPN。

依照Tensorflow的官方文件 在docker中安裝Tensorflow的時候,國內的使用者通常會報錯,有的藉助VPN可以解決,而有的不行。

(1)在docker成功安裝完後,在終端命令列輸入:

sudo docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow

(2)報錯如下:

Unable to find image 'gcr.io/tensorflow/tensorflow:latest' locally
docker: Error response from daemon: Get https://gcr.io/v1/_ping: dial tcp 64.233.188.82:443: i/o timeout.
See 'docker run --help'.

主要原因還是因為GFW,在Github上有人提出過引起這個問題的原因,tensorflow/issues/1273,

點選此連結

(3)關於這個,問題,我覺得最簡單的辦法是更換映象的pull映象庫。也就是說,不是從Tensorflow給出的庫(Google Cloud Platform)進行pull,而是用docker的庫(docker hub)。

因此,在終端輸入如下命令:

sudo docker run -it -p 8888:8888 tensorflow/tensorflow

只要你的docker是安裝成功,能夠pull映象,那麼基本會成功安裝Tensorflow。我的執行輸出如下:

Unable to find image 'tensorflow/tensorflow:latest'
locally latest: Pulling from tensorflow/tensorflow 862a3e9af0ae: Pull complete 6498e51874bf: Pull complete 159ebdd1959b: Pull complete 0fdbedd3771a: Pull complete 7a1f7116d1e3: Pull complete f22ce26e7804: Pull complete 80e54362977d: Pull complete 6bf17916f3f1: Pull complete cbb2cc9179cb: Pull complete 4f976cd18afd: Pull complete 31ba02bae790: Pull complete e26c94fb0976: Pull complete Digest: sha256:feedf027da0d525300dc73e433b4ade2147c6a408756cdd9846fd37b40929f8a Status: Downloaded newer image for tensorflow/tensorflow:latest [I 03:19:59.901 NotebookApp] Writing notebook server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret [W 03:19:59.981 NotebookApp] WARNING: The notebook server is listening on all IP addresses and not using encryption. This is not recommended. [I 03:20:00.015 NotebookApp] Serving notebooks from local directory: /notebooks [I 03:20:00.015 NotebookApp] 0 active kernels [I 03:20:00.015 NotebookApp] The Jupyter Notebook is running at: http://[all ip addresses on your system]:8888/?token=93a4eec743c0601c77e6b3f88386da5efab335f49d6a476e [I 03:20:00.015 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation). [C 03:20:00.016 NotebookApp] Copy/paste this URL into your browser when you connect for the first time, to login with a token: http://localhost:8888/?token=93a4eec743c0601c77e6b3f88386da5efab335f49d6a476e [I 03:25:55.708 NotebookApp] 302 GET /?token=93a4eec743c0601c77e6b3f88386da5efab335f49d6a476e (172.17.0.1) 0.45ms

因為這個映象比較大,所以會需要一定的時間pull,耐心等待就好。

(4)開啟一個新的命令終端進行測試是否安裝成功:

首先,檢視docker中有哪些容器/映象存在

sudo docker ps -a

得到如下格式的輸出:
這裡寫圖片描述
注意到,第一個容器即是我們安裝的tensorflow的映象在執行的容器,其ID是53f212117a94

接著,進入容器:
替換我的這個53f212117a94 為你的,其他命令不變

sudo docker exec -i -t 53f212117a94 /bin/bash

得到輸入如下:

mingchen@mingchen-HP:~$ sudo docker exec -i -t 53f212117a94 /bin/bash
root@53f212117a94:/notebooks# 

看看python版本:

root@53f212117a94:/notebooks# 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.

輸出Hello, TensorFlow!:

>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))
Hello, TensorFlow!

簡單計算:

>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> print(sess.run(a + b))
42

測試結果顯示,已成功在docker中安裝Tensorflow。

祝大家好運!