如何运行一个新的Jupyter Notebook文件,它不是Docker中预先建立的码头图像的一部分? [英] How to run a new Jupyter Notebook file that's not part of a pre-built docker image in docker?
问题描述
为了处理作业,我遵循
然而,我现在想要运行的课程最终项目是不是预先制作的Udacity泊坞窗影像的一部分。我怎样才能做到这一点? 最后的项目可以在这里找到,使用digit_recognition .ipynb特别是在docker中运行的文件。
任何指导都非常感谢。
一种替代方法就是这样:
- 只需像这样启动你的容器:$ docker start -ai
tensorflow-udacity - 然后,单击上传按钮,找到最终的
项目iPython Notebook文件并上传。
就是这样。无论您所做的更改将被保留,您将可以在容器中查看新文件!
I am new to Docker. In order to take the Udacity Deep Learning course, I had to set up TensorFlow on my Windows machine using Docker. (Although TensorFlow is now available on Windows, it only supports Python 3.5, however the Udacity course material requires Python 2.7. Therefore, I have to stick with the Docker way of using TensorFlow.)
To work on the assignments, I followed the instructions here as detailed below:
- First, I installed docker toolbox.
- Then, I launch Docker using the Docker Quickstart Terminal. For the first time, I ran:
docker run -p 8888:8888 --name tensorflow-udacity -it gcr.io/tensorflow/udacity-assignments:0.6.0
.
Each time after, I just run this in my docker terminal:
docker start -ai tensorflow-udacity
- Finally, in the address bar, with
http://192.168.99.100:8888
I get the assignment Jupyter notebooks up and running (see image below).
However, what I want now is to run the final project of the course which is not part of the pre-built Udacity docker image. How can I do that? The final project can be found here, with the "digit_recognition.ipynb" specifically being the file to run in docker.
Any guidance is much appreciated.
An alternative and much easier way is this:
- Just start up your container like this: $ docker start -ai tensorflow-udacity
- Then, click the upload button and locate the final project iPython Notebook file and upload it.
That's it. Whatever changes you make will be retained and you'll be able to see the new file in the container going forward!
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