hello_world_model.md

Training a Hello World segmentation model

In the configs folder, you will find a config file called HelloWorld.py We have created this file to demonstrate how to:

1. Subclass SegmentationModelBase which is the base config for all segmentation model configs
2. Configure the UNet3D implemented in this package
3. Configure Azure HyperDrive based parameter search

• This model can be trained from the commandline, from the root of the repo: python InnerEye/ML/runner.py --model=HelloWorld
• If you want to test your AzureML workspace with the HelloWorld model:
  • Make sure your AzureML workspace has been set up. You should have inside the folder InnerEye a settings.yml file that specifies the datastore, the resource group, and the workspace on which to run
  • Upload to datasets storage account for your AzureML workspace: Tests/ML/test_data/dataset.csv and Test/ML/test_data/train_and_test_data and name the folder "hello_world"
  • If you have set up AzureML then parameter search can be performed for this model by running: python InnerEye/ML/runner.py --model=HelloWorld --azureml --hyperdrive