mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-05-02 02:29:16 -05:00
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)
66 lines
1.6 KiB
Markdown
66 lines
1.6 KiB
Markdown
# TinyTorch Research Paper
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Complete LaTeX source for the TinyTorch research paper.
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---
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## Files
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- **[paper.tex](paper.tex)** - Main paper (~12-15 pages, two-column format)
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- **[references.bib](references.bib)** - Bibliography (22 references)
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- **[compile_paper.sh](compile_paper.sh)** - Build script (requires LaTeX installation)
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---
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## Quick Start: Get PDF
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### Option 1: Overleaf (Recommended)
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1. Go to [Overleaf.com](https://www.overleaf.com)
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2. Create free account
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3. Upload `paper.tex` and `references.bib`
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4. Click "Recompile"
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5. Download PDF
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### Option 2: Local Compilation
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```bash
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./compile_paper.sh
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```
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Requires LaTeX installation (MacTeX or BasicTeX).
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---
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## Paper Details
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- **Format**: Two-column LaTeX (conference-standard)
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- **Length**: ~12-15 pages
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- **Sections**: 7 complete sections
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- **Tables**: 3 (framework comparison, learning objectives, performance benchmarks)
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- **Code listings**: 5 (syntax-highlighted Python examples)
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- **References**: 22 citations
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---
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## Key Contributions
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1. **Progressive disclosure via monkey-patching** - Novel pedagogical pattern
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2. **Systems-first curriculum design** - Memory/FLOPs from Module 01
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3. **Historical milestone validation** - 70 years of ML as learning modules
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4. **Constructionist framework building** - Students build complete ML system
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Framed as design contribution with empirical validation planned for Fall 2025.
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---
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## Submission Venues
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- **ArXiv** - Immediate (establish priority)
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- **SIGCSE 2026** - August deadline (may need 6-page condensed version)
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- **ICER 2026** - After classroom data (full empirical study)
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---
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Ready for submission! Upload to Overleaf to get your PDF.
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