This script shows example usage of the Determined Python SDK to run and administer experiments.
It:
- Archives any existing experiments with the same names as the datasets we'll train on.
- Creates models for each dataset and registers them in the Determined model registry.
- Trains a model for each dataset by creating an experiment.
- Registers the best checkpoint for each experiment in the Determined model registry.
For an in-depth discussion of this script, see the blog post: https://www.determined.ai/blog/python-sdk
For more information on the Determined Python SDK, see: https://docs.determined.ai/latest/reference/python-sdk.html
To run this demo:
- Install dependencies. In addition to the determined CLI, we this demo uses MedMNIST datasets.
pip install -r requirements.txt
- Set DET_MASTER environment variable. For example, if you're running this locally:
export DET_MASTER=localhost:8080
For more information about configuring the CLI, see this doc.
- Now the demo is ready to be executed. To run experiments:
python determined_sdk_demo.py
The code in the medmnist_model
directory is based on the determined_medmnist_e2e
repo by Isha Ghodgaonkar.