From 8c5921a6d0f1abe73a7033cddbc13b9030d7efd3 Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Tue, 16 Sep 2025 10:12:33 -0400 Subject: [PATCH] Restructure course to start with hands-on Module 0: Setup MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Moved Introduction to "Course Orientation" section (no longer Module 0) - Renumbered all modules: Setup becomes Module 0, course now has 16 modules - Updated table of contents to separate orientation from formal course modules - Updated intro.md and vision.md to reflect 16 modules instead of 17 - Course now starts immediately with hands-on implementation (Setup) - Maintains Buildβ†’Useβ†’Reflect philosophy by removing non-implementation module - Introduction remains accessible as orientation material without being numbered module --- book/_toc.yml | 39 +++++++++++++++++++++------------------ book/intro.md | 22 +++++++++++----------- book/vision.md | 2 +- 3 files changed, 33 insertions(+), 30 deletions(-) diff --git a/book/_toc.yml b/book/_toc.yml index 14ca8eca..01e4a189 100644 --- a/book/_toc.yml +++ b/book/_toc.yml @@ -17,54 +17,57 @@ parts: - file: instructor-guide title: "πŸ“š Instructor Guide" -- caption: Foundation +- caption: Course Orientation chapters: - file: chapters/00-introduction - title: "0. Introduction" + title: "Introduction" + +- caption: Foundation + chapters: - file: chapters/01-setup - title: "1. Setup" + title: "0. Setup" - file: chapters/02-tensor - title: "2. Tensors" + title: "1. Tensors" - file: chapters/03-activations - title: "3. Activations" + title: "2. Activations" - caption: Building Blocks chapters: - file: chapters/04-layers - title: "4. Layers" + title: "3. Layers" - file: chapters/05-dense - title: "5. Dense" + title: "4. Dense" - file: chapters/06-spatial - title: "6. Spatial" + title: "5. Spatial" - file: chapters/07-attention - title: "7. Attention" + title: "6. Attention" - caption: Training Systems chapters: - file: chapters/08-dataloader - title: "8. DataLoader" + title: "7. DataLoader" - file: chapters/09-autograd - title: "9. Autograd" + title: "8. Autograd" - file: chapters/10-optimizers - title: "10. Optimizers" + title: "9. Optimizers" - file: chapters/11-training - title: "11. Training" + title: "10. Training" - caption: Inference & Serving chapters: - file: chapters/12-compression - title: "12. Compression" + title: "11. Compression" - file: chapters/13-kernels - title: "13. Kernels" + title: "12. Kernels" - file: chapters/14-benchmarking - title: "14. Benchmarking" + title: "13. Benchmarking" - file: chapters/15-mlops - title: "15. MLOps" + title: "14. MLOps" - caption: Capstone Project chapters: - file: chapters/16-capstone - title: "16. Capstone" + title: "15. Capstone" - caption: Additional Resources chapters: diff --git a/book/intro.md b/book/intro.md index 08dc8c45..51d250a5 100644 --- a/book/intro.md +++ b/book/intro.md @@ -147,39 +147,39 @@ After TinyTorch, you'll be the person your team asks: --- -## πŸ“š **Course Journey: 17 Modules** +## πŸ“š **Course Journey: 16 Modules** ```{admonition} πŸ—οΈ Foundation :class: note -**0. Introduction** β€’ **1. Setup** β€’ **2. Tensors** β€’ **3. Activations** +**0. Setup** β€’ **1. Tensors** β€’ **2. Activations** -System overview, development workflow, multi-dimensional arrays, and mathematical functions that enable learning. +Development workflow, multi-dimensional arrays, and mathematical functions that enable learning. ``` ```{admonition} 🧱 Building Blocks :class: note -**4. Layers** β€’ **5. Dense** β€’ **6. Spatial** β€’ **7. Attention** +**3. Layers** β€’ **4. Dense** β€’ **5. Spatial** β€’ **6. Attention** Dense layers, sequential networks, convolutional operations, and self-attention mechanisms with memory analysis. ``` ```{admonition} 🎯 Training Systems :class: note -**8. DataLoader** β€’ **9. Autograd** β€’ **10. Optimizers** β€’ **11. Training** +**7. DataLoader** β€’ **8. Autograd** β€’ **9. Optimizers** β€’ **10. Training** CIFAR-10 loading, automatic differentiation with graph management, SGD/Adam with memory profiling, and complete training orchestration. ``` ```{admonition} πŸš€ Production Systems :class: note -**12. Compression** β€’ **13. Kernels** β€’ **14. Benchmarking** β€’ **15. MLOps** +**11. Compression** β€’ **12. Kernels** β€’ **13. Benchmarking** β€’ **14. MLOps** Model optimization, high-performance operations, systematic evaluation, and production monitoring with real deployment patterns. ``` ```{admonition} πŸŽ“ Capstone Project :class: note -**16. Integration Engineering** +**15. Integration Engineering** Choose your specialization: performance optimization, algorithm extensions, systems engineering, benchmarking analysis, or developer tools. ``` @@ -188,18 +188,18 @@ Choose your specialization: performance optimization, algorithm extensions, syst ## πŸ”— **Complete System Integration** -**This isn't 14 separate exercises.** Every component you build integrates into one fully functional ML framework: +**This isn't 15 separate exercises.** Every component you build integrates into one fully functional ML framework: ```{admonition} 🎯 How It All Connects :class: important -**Module 2: Your Tensor class** β†’ **Module 3: Powers your activation functions** β†’ **Module 4: Enables your layers** β†’ **Module 5: Forms your networks** β†’ **Module 8: Drives your autograd system** β†’ **Module 9: Optimizes with your SGD/Adam** β†’ **Module 10: Trains on real CIFAR-10 data** +**Module 1: Your Tensor class** β†’ **Module 2: Powers your activation functions** β†’ **Module 3: Enables your layers** β†’ **Module 4: Forms your networks** β†’ **Module 7: Drives your autograd system** β†’ **Module 8: Optimizes with your SGD/Adam** β†’ **Module 9: Trains on real CIFAR-10 data** **Result:** A complete, working ML framework that you built from scratch, capable of training real neural networks on real datasets. ``` ### **🎯 Capstone: Optimize Your Framework** -After completing the 14 core modules, you have a **complete ML framework**. Now make it better through systems engineering: +After completing the 15 core modules, you have a **complete ML framework**. Now make it better through systems engineering: **Choose Your Focus:** - ⚑ **Performance Optimization**: GPU kernels, vectorization, memory-efficient operations @@ -228,7 +228,7 @@ After completing the 14 core modules, you have a **complete ML framework**. Now *"I want to build this myself"* - Fork the repo and work locally with full development environment - Build complete ML framework from scratch with `tito` CLI -- 14 progressive assignments from setup to production MLOps +- 15 progressive assignments from setup to production MLOps - Professional development workflow with automated testing ### **πŸ‘¨β€πŸ« [Classroom Use](usage-paths/classroom-use.md)** *(Instructors)* diff --git a/book/vision.md b/book/vision.md index f823b6da..f088ec0f 100644 --- a/book/vision.md +++ b/book/vision.md @@ -155,7 +155,7 @@ ML Systems Thinking sections in every module: - Connection to industry practices and framework design decisions **🎯 Complete Integration** -- 17 modules that build ONE cohesive ML framework +- 16 modules that build ONE cohesive ML framework - Each component integrates with others (not isolated exercises) - Professional package structure with CLI tools and testing