Build PyTorch to Understand PyTorch
summary
TinyTorch is a 20-module curriculum that has learners implement a PyTorch-like framework in pure Python tensor + autograd with unit tests that export working code into a shared repo. Modules start profiling from Module 01 and use build‑to‑validate milestones to recreate ML history (Perceptron → CNNs → Transformers) and run MLPerf‑style benchmarks. Specific results reported: Adam uses about 3× the memory of SGD, a KV cache change yields an 11× speedup for a tiny GPT, and a small GPT trained on student code can reverse text sequences.
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chapters (6)
- 0:00Introduction
- 4:41Tiny Torch overview
- 9:50First module walkthrough
- 12:41Advanced modules
- 14:30Key takeaways and call to action
- 17:19AI engineering impact
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