Following the feedback from lab 1, we have made some changes to the installation procedure.
You can now use either Anaconda version 2 or 3 to create virtual environments for Machine Translation lab work.
Importantly, we are aligning more closely to the setup of the MLP course. The MLP github page includes detailed instructions for setting up Anaconda and Jupyter notebooks. However, please note that the environment names, packages and the python versions used may differ.
Anaconda should be setup on your DICE machines if you followed along lab 1
If not installed, instructions are as follows:
Open a terminal on the DICE machine and then type the following command:
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
We will create a new environment for python 3 using conda. These commands will work with both Anaconda 2 and 3.
Create the environment and install packages by entering the command:
conda create --name mtenv python=3
source activate mtenv
conda install seaborn pandas jupyter matplotlib
pip install tqdm
pip install chainer
conda clean -t
Download the lab materials
git clone https://github.com/INFR11133/lab2.git
cd lab2
Start Jupyter notebook by entering the command:
jupyter notebook
Open the notebook char_language_model.ipynb
The datasets for this lab are:
data/mickiewicz.txt
data/tinyshakespeare.txt