pip install -e .
python -m unittest
python -m unittest test.test_bpe
From the top-most directory, run the following in a Terminal:
mkdir results
python ozone/experiment.py config/default.config.json results/default.trial1.json
It should hopefully take 1500-2500 epochs to reach a test performance exceeding 98%, at which point training will stop. Then you can graph the results inside of an interactive Python interpreter:
from ozone.train import *
graph_results('results/default.trial1.json')
docker build --tag mhrmm/ozone:1.1 .
Upon logging into a new Unix machine, do the following:
Install Docker:
curl -sSL https://get.docker.com/ | sh
Get the Docker image from Dockerhub:
sudo docker pull mhrmm/ozone:1.1
Run the Docker image using CPU:
sudo docker run mhrmm/ozone:1.1 config/default.config.json default.trial1.json
Run the Docker image using GPUs (if on a GPU machine):
sudo docker run --gpus all mhrmm/ozone:1.1 config/default.config.json default.trial1.json
Each training should take between 5-20 minutes, depending on the machine. Before running the full script, you can check to see whether the Docker image will run successfully by calling it without arguments, e.g. one of the following two commands:
sudo docker run mhrmm/ozone:1.1
sudo docker run --gpus all mhrmm/ozone:1.1
This should generate the following error, which simply says that the argument (dog.n.01.json) is missing:
Traceback (most recent call last):
File "/app/ozone/train.py", line 264, in <module>
baseline_experiment(filename)
File "/app/ozone/train.py", line 255, in baseline_experiment
run_multiple(filename, configs)
File "/app/ozone/train.py", line 201, in run_multiple
assert(experiment_log.endswith('.exp.json'))