Unit tests have been implemented for classes and functions that relate to Deep Learning tasks such as defining Models, Hyperparameters, Datasets / Dataloaders, as well as the training process.

The process is documented in the following notion file:
https://www.notion.so/qim-dtu/Unit-tests-to-DL-funtions-e8ad1fc1aa134da2ab26474cc6480ca2

the following scripts have been made under qim3d/tests/:

• models/test_unet.py (unit tests for UNet() and Hyperparameters())
• utils/test_augmentations.py (unit tests for Augmentations() and ValueErrors)
• utils/test_data.py (unit tests for Dataset() class, resizing of images with crop, padding, prepare_datasets() and prepare_dataloaders())
• utils/test_models.py (unit tests for output of model_summary() and inference())

Problem:

• Some deep learning tests require considerably more time to run (around 15s to 20s) especially when a Dataloader is involved. This is the case for prepare_dataloaders() as well as the model_summary(). Should they still be included?
• I couldn't think of a way to test the train_model() function, since that requires training a DL model, and would also take too much time.