The Informatics computing labs use DICE, a Linux environment If you are not familiar with Linux and its basic usage, you can find help on this webpage.
The labs all use Python within a Jupyter notebook that you can edit in your web browser. If you are experienced with Python programming and prefer to edit code directly in your own development tool, this is fine too.
Each lab week has its own Jupyter notebook, with the exception of Labs 3 and 4 which share a notebook. They are contained within files named asr_labX.ipynb
At the start of first lab, you need to set up your Python environment. This can be used for subsequent weeks of labs, so these commands only need to be run once.
Here are the commands for setting up the environment. These commands have been tested on DICE, but work in most other computing environments (with possible minor changes)
git clone https://github.com/ZhaoZeyu1995/asr_labs.git
cd asr_labs
source /opt/conda/etc/profile.d/conda.sh
conda create -n asr_env python=3.7
conda activate asr_env
pip install openfst-python jupyterNOTE: You will need to run some other commands to sync later weeks’ lab exercises when they become available.
- Log in to a computer with your DICE account and password
- Run the commands for setting up the environment above.
Now we have set up the environment for our labs. From now on, every time we log in, we just need to run the following commands.
source /opt/conda/etc/profile.d/conda.sh
cd asr_labs ## if you are not in this directory already
conda activate asr_env
jupyter notebookAfter running the last command, the default browser will be opened automatically and you can view and open all the files with Jupyter notebook.
At first, the only the notebook for Lab 1 will be available -- in later weeks, you will need to run the command git pull in the asr_labs directory to update your working copy with the latest lab exercises from the repository. This will also allow you to obtain the solutions, and any file amendments or bug fixes.
If you are not familiar with Git, the safest thing to do is to make a copy of the file you would like to edit (e.g. to make a copy of asr_lab1.ipynb, you can run cp asr_lab1.ipynb asr_lab1_copied.ipynb) and only make changes and run the code in the copied files (asr_lab1_copied.ipynb in the example).
To get updates, all you need to do is to run git pull in the asr_labs directory (of course, you will have to cd to this directory first).
You are recommended to run git pull every time you cd asr_labs to obtain the latest files.
NOTE: When you run git pull, in certain circumstances you may get an error as below
error: Your local changes to the following files would be overwritten by merge:
asr_lab1.ipynb
Please commit your changes or stash them before you merge.
Aborting
In this case, you can run
git stash
which stashes your changes to this repository.
After that, you can run
git pull
git stash pop
which will update your local version to the one on Github and then merge the changes you made. You can view all the changes we made and the new files we uploaded to the repository on your machine now. If you continue to receive warning or error messages at this stage, please seek the advice of a lab demonstrator.
NOTE: If you are not familiar with Git is safest to create a backup copy of all your files before doing this.
If you are an experienced Python developer and prefer to work directly in Python instead of in the notebook, this is fine. To convert the notebook to pure Python code, use
jupyter nbconvert --to python asr_labX.ipynb
replacing the final argument with the name of the notebook you wish to convert.
Although it's not recommended until you have become familiar with the working environment for the labs, it is possible to access them for a remote working. Please refer to Remote Working