Training Loop Anatomy
Every deep learning project, regardless of architecture or task, runs the same twenty-odd lines at its core: forward, compute loss, zero the gradients, backward, step. That order is not negotiable — get it wrong and training either does nothing or does something subtly incorrect, and both failure modes tend to fail quietly rather than crash loudly.