5 Commits

Author	SHA1	Message	Date
Vijay Janapa Reddi	bd7fcb2177	Release preparation: fix package exports, tests, and documentation ... Package exports: - Fix tinytorch/__init__.py to export all required components for milestones - Add Dense as alias for Linear for compatibility - Add loss functions (MSELoss, CrossEntropyLoss, BinaryCrossEntropyLoss) - Export spatial operations, data loaders, and transformer components Test infrastructure: - Create tests/conftest.py to handle path setup - Create tests/test_utils.py with shared test utilities - Rename test_progressive_integration.py files to include module number - Fix syntax errors in test files (spaces in class names) - Remove stale test file referencing non-existent modules Documentation: - Update README.md with correct milestone file names - Fix milestone requirements to match actual module dependencies Export system: - Run tito export --all to regenerate package from source modules - Ensure all 20 modules are properly exported	2025-12-02 14:19:56 -05:00
Vijay Janapa Reddi	d3a126235c	Restructure: Separate developer source (src/) from learner notebooks (modules/) ... Major directory restructure to support both developer and learner workflows: Structure Changes: - NEW: src/ directory for Python source files (version controlled) - Files renamed: tensor.py → 01_tensor.py (matches directory naming) - All 20 modules moved from modules/ to src/ - CHANGED: modules/ now holds generated notebooks (gitignored) - Generated from src/*.py using jupytext - Learners work in notebooks, developers work in Python source - UNCHANGED: tinytorch/ package (still auto-generated from notebooks) Workflow: src/*.py → modules/*.ipynb → tinytorch/*.py Command Updates: - Updated export command to read from src/ and generate to modules/ - Export flow: discovers modules in src/, converts to notebooks in modules/, exports to tinytorch/ - All 20 modules tested and working Configuration: - Updated .gitignore to ignore modules/ directory - Updated README.md with new three-layer architecture explanation - Updated export.py source mappings and paths Benefits: - Clean separation: developers edit Python, learners use notebooks - Better version control: only Python source committed, notebooks generated - Flexible learning: can work in notebooks OR Python source - Maintains backward compatibility: tinytorch package unchanged Tested: - Single module export: tito export 01_tensor ✅ - All modules export: tito export --all ✅ - Package imports: from tinytorch.core.tensor import Tensor ✅ - 20/20 modules successfully converted and exported	2025-11-25 00:02:21 -05:00
Vijay Janapa Reddi	763cdd2bf2	Implement Tensor slicing with progressive disclosure and fix embedding gradient flow ... WHAT: Added Tensor.__getitem__ (slicing) following progressive disclosure principles MODULE 01 (Tensor): - Added __getitem__ method for basic slicing operations - Clean implementation with NO gradient mentions (progressive disclosure) - Supports all NumPy-style indexing: x[0], x[:3], x[1:4], x[:, 1] - Ensures scalar results are wrapped in arrays MODULE 05 (Autograd): - Added SliceBackward function for gradient computation - Implements proper gradient scatter: zeros everywhere except sliced positions - Added monkey-patching in enable_autograd() for __getitem__ - Follows same pattern as existing operations (add, mul, matmul) MODULE 11 (Embeddings): - Updated PositionalEncoding to use Tensor slicing instead of .data - Fixed multiple .data accesses that broke computation graphs - Removed Tensor() wrapping that created gradient-disconnected leafs - Uses proper Tensor operations to preserve gradient flow TESTING: - All 6 component tests PASS (Embedding, Attention, FFN, Residual, Forward, Training) - 19/19 parameters get gradients (was 18/19 before) - Loss dropping better: 1.54→1.08 (vs 1.62→1.24 before) - Model still not learning (0% accuracy) - needs fresh session to test monkey-patching WHY THIS MATTERS: - Tensor slicing is FUNDAMENTAL - needed by transformers for position embeddings - Progressive disclosure maintains educational integrity - Follows existing TinyTorch architecture patterns - Enables position embeddings to potentially learn (pending verification) DOCUMENTS CREATED: - milestones/05_2017_transformer/TENSOR_SLICING_IMPLEMENTATION.md - milestones/05_2017_transformer/STATUS.md - milestones/05_2017_transformer/FIXES_SUMMARY.md - milestones/05_2017_transformer/DEBUG_REVERSAL.md - tests/milestones/test_reversal_debug.py (component tests) ARCHITECTURAL PRINCIPLE: Progressive disclosure is not just nice-to-have, it's CRITICAL for educational systems. Don't expose Module 05 concepts (gradients) in Module 01 (basic operations). Monkey-patch when features are needed, not before.	2025-11-22 18:26:12 -05:00
Vijay Janapa Reddi	96880b3133	Update tinytorch and tito with module exports ... Re-exported all modules after restructuring: - Updated _modidx.py with new module locations - Removed outdated autogeneration headers - Updated all core modules (tensor, autograd, layers, etc.) - Updated optimization modules (quantization, compression, etc.) - Updated TITO commands for new structure Changes include: - 24 tinytorch/ module files - 24 tito/ command and core files - Updated references from modules/source/ to modules/ All modules re-exported via nbdev from their new locations.	2025-11-10 19:42:03 -05:00
Vijay Janapa Reddi	f4fdf968c5	feat: add exported packages for benchmarking, competition, and data utilities ... - tinytorch/benchmarking/: Benchmark class for Module 19 - tinytorch/competition/: Submission utilities for Module 20 - tinytorch/data/: Data loading utilities - tinytorch/utils/data/: Additional data helpers Exported from modules 19-20 and module 08	2025-11-09 14:42:23 -05:00