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Classy Pipeline

Explore how to create a structured pipeline in PyTorch by combining data preparation, model configuration, and training within a custom class. Understand how this approach improves code organization and efficiency while maintaining control over model components and training steps.

Pipeline steps

In the chapter, Rethinking the Training Loop, our pipeline was composed of three steps: data preparation V2, model configuration V3, and model training V5. The last step, model training, has already been integrated into our StepByStep class. Let us take a look at the other two steps:

But before that, let us generate our synthetic data once again.

Shell
# Runs data generation - so we do not need to copy code here
%run -i data_generation/simple_linear_regression.py

This will have the ...