We recommend developing code on an EC2 instance with a GPU. We use p3.8xlarge as it has a large amount of memory and 4 GPUs which enables fast training.
- Copy the ReFinED code to your machine
git clone https://github.com/amazon-science/ReFinED.git
. - Use your preferred IDE (such as PyCharm) to modify the code.
- Copy the ReFinED code to your EC2 instance
rsync -zarv --prune-empty-dirs --include "*/" --include "*.py" --exclude="*" ReFinED/ ubuntu@X.XXX.XXX.XX:/path_to_code/
. - Add a new host to your ssh config file so that you do not need to provide the path to the private ssh key each time you connect or copy data (~/.ssh/config) example:
Host x.xxx.xxx.xxx
User ubuntu
IdentityFile <path_to_ssh_private_key_file>
- SSH into your EC2 instance.
- Install the Python dependencies using
pip install -r requirements.txt
. - Add ReFinED to your Python path
export PYTHONPATH=$PYTHONPATH:/<path_to_code>/src/
. - To confirm the setup is correct run
python example_scripts/refined_demo.py
runs successfully.