This PR changes the codepath so all models trained on AzureML are registered. The codepath previously allowed only segmentation models (subclasses of `SegmentationModelBase`) to be registered. Models are registered after a training run or if the `only_register_model` flag is set. Models may be legacy InnerEye config-based models or may be defined using the LightningContainer class.
The PR also removes the AzureRunner conda environment. The full InnerEye conda environment is needed to submit a training job to AzureML.
It splits the `TrainHelloWorldAndHelloContainer` job in the PR build into two jobs, `TrainHelloWorld` and `TrainHelloContainer`. It adds a pytest marker `after_training_hello_container` for tests that can be run after training is finished in the `TrainHelloContainer` job.
This will solve the issue of model registration in #377 and #398.
- The use_gpu flag for container models was not picked up correctly, always running without GPU
- When running inference for container models with the test_step method, PL would fail when running on >1 GPU
- Adds an extra test to run the HelloContainer model in AzureML
Shruthi42
Anton Schwaighofer
David Carter