4. Testing
The same trend is followed when testing ML systems. Hence, we must test our application across all three dimensions: the data, the model, and the code. We must also ensure that the feature, training, and inference pipeline are well integrated with external services, such as the feature store, and work together as a system. When working with Python, the most common tool to write your tests is pytest, which we also recommend.
Test types
In the development cycle, six primary types of tests are commonly employed at various stages:
- Unit tests: These tests focus on individual components with a single responsibility, such as a function that adds two tensors or one that finds an element in a list.
- Integration tests: These tests evaluate the interaction between integrated components or units within a system, such as the data evaluation pipeline or the feature engineering pipeline, and how they are integrated with the data warehouse and feature store. ...
