Build reproducible PyTorch models

Write reproducible PyTorch models and training loops

Building deep learning code that runs reproducibly across devices and captures shape contracts explicitly

• · model architecture sketch
• · dataset schema

• · nn.Module class
• · training loop code

• · torch
• · torch.cuda

CUDA/MPS available for device-agnostic code

• · Hardcoded device crashes on CPU-only machines
• · Non-deterministic weight init across runs
• · GPU OOM from untracked tensor shapes

• · Device-agnostic code pattern
• · Explicit seed management
• · Shape annotations in forward()