mirror of
https://github.com/harvard-edge/cs249r_book.git
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c602f97364
TinyTorch educational deep learning framework now lives at tinytorch/
Structure:
- tinytorch/src/ - Source modules (single source of truth)
- tinytorch/tito/ - CLI tool
- tinytorch/tests/ - Test suite
- tinytorch/site/ - Jupyter Book website
- tinytorch/milestones/ - Historical ML implementations
- tinytorch/datasets/ - Educational datasets (tinydigits, tinytalks)
- tinytorch/assignments/ - NBGrader assignments
- tinytorch/instructor/ - Teaching materials
Workflows (with tinytorch- prefix):
- tinytorch-ci.yml - CI/CD pipeline
- tinytorch-publish-dev.yml - Dev site deployment
- tinytorch-publish-live.yml - Live site deployment
- tinytorch-build-pdf.yml - PDF generation
- tinytorch-release-check.yml - Release validation
Repository Variables added:
- TINYTORCH_ROOT = tinytorch
- TINYTORCH_SRC = tinytorch/src
- TINYTORCH_SITE = tinytorch/site
- TINYTORCH_TESTS = tinytorch/tests
All workflows use \${{ vars.TINYTORCH_* }} for path configuration.
Note: tinytorch/site/_static/favicon.svg kept as SVG (valid for favicons)
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TinyTorch Research Paper
Complete LaTeX source for the TinyTorch research paper.
Files
- paper.tex - Main paper (~12-15 pages, two-column format)
- references.bib - Bibliography (22 references)
- compile_paper.sh - Build script (requires LaTeX installation)
Quick Start: Get PDF
Option 1: Overleaf (Recommended)
- Go to Overleaf.com
- Create free account
- Upload
paper.texandreferences.bib - Click "Recompile"
- Download PDF
Option 2: Local Compilation
./compile_paper.sh
Requires LaTeX installation (MacTeX or BasicTeX).
Paper Details
- Format: Two-column LaTeX (conference-standard)
- Length: ~12-15 pages
- Sections: 7 complete sections
- Tables: 3 (framework comparison, learning objectives, performance benchmarks)
- Code listings: 5 (syntax-highlighted Python examples)
- References: 22 citations
Key Contributions
- Progressive disclosure via monkey-patching - Novel pedagogical pattern
- Systems-first curriculum design - Memory/FLOPs from Module 01
- Historical milestone validation - 70 years of ML as learning modules
- Constructionist framework building - Students build complete ML system
Framed as design contribution with empirical validation planned for Fall 2025.
Submission Venues
- ArXiv - Immediate (establish priority)
- SIGCSE 2026 - August deadline (may need 6-page condensed version)
- ICER 2026 - After classroom data (full empirical study)
Ready for submission! Upload to Overleaf to get your PDF.