Vijay Janapa Reddi
e82bc8ba97
Complete comprehensive system validation and cleanup
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🎯 Major Accomplishments:
• ✅ All 15 module dev files validated and unit tests passing
• ✅ Comprehensive integration tests (11/11 pass)
• ✅ All 3 examples working with PyTorch-like API (XOR, MNIST, CIFAR-10)
• ✅ Training capability verified (4/4 tests pass, XOR shows 35.8% improvement)
• ✅ Clean directory structure (modules/source/ → modules/)
🧹 Repository Cleanup:
• Removed experimental/debug files and old logos
• Deleted redundant documentation (API_SIMPLIFICATION_COMPLETE.md, etc.)
• Removed empty module directories and backup files
• Streamlined examples (kept modern API versions only)
• Cleaned up old TinyGPT implementation (moved to examples concept)
📊 Validation Results:
• Module unit tests: 15/15 ✅
• Integration tests: 11/11 ✅
• Example validation: 3/3 ✅
• Training validation: 4/4 ✅
🔧 Key Fixes:
• Fixed activations module requires_grad test
• Fixed networks module layer name test (Dense → Linear)
• Fixed spatial module Conv2D weights attribute issues
• Updated all documentation to reflect new structure
📁 Structure Improvements:
• Simplified modules/source/ → modules/ (removed unnecessary nesting)
• Added comprehensive validation test suites
• Created VALIDATION_COMPLETE.md and WORKING_MODULES.md documentation
• Updated book structure to reflect ML evolution story
🚀 System Status: READY FOR PRODUCTION
All components validated, examples working, training capability verified.
Test-first approach successfully implemented and proven.
2025-09-23 10:00:33 -04:00
Vijay Janapa Reddi
791d1e3153
Update generated notebooks and package exports
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- Regenerate all .ipynb files from fixed .py modules
- Update tinytorch package exports with corrected implementations
- Sync package module index with current 16-module structure
These generated files reflect all the module fixes and ensure consistent
.py ↔ .ipynb conversion with the updated module implementations.
2025-09-18 16:42:57 -04:00
Vijay Janapa Reddi
f9309e8b9d
🔧 Complete module restructuring and integration fixes
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📦 Module File Organization:
- Renamed networks_dev.py → dense_dev.py in 05_dense module
- Renamed cnn_dev.py → spatial_dev.py in 06_spatial module
- Added new 07_attention module with attention_dev.py
- Updated module.yaml files to reference correct filenames
- Updated #| default_exp directives for proper package exports
🔄 Core Package Updates:
- Added tinytorch.core.dense (Sequential, MLP architectures)
- Added tinytorch.core.spatial (Conv2D, pooling operations)
- Added tinytorch.core.attention (self-attention mechanisms)
- Updated all core modules with latest implementations
- Fixed tensor assignment issues in compression module
🧪 Test Integration Fixes:
- Updated integration tests to use correct module imports
- Fixed tensor activation tests for new module structure
- Ensured compatibility with renamed components
- Maintained 100% individual module test success rate
Result: Complete 14-module TinyTorch framework with proper organization,
working integrations, and comprehensive test coverage ready for production use.
2025-07-18 02:10:49 -04:00
Vijay Janapa Reddi
05391eb550
feat: Restructure integration tests and optimize module timing
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- Flattened tests/ directory structure (removed integration/ and system/ subdirectories)
- Renamed all integration tests with _integration.py suffix for clarity
- Created test_utils.py with setup_integration_test() function
- Updated integration tests to use ONLY tinytorch package imports
- Ensured all modules are exported before running tests via tito export --all
- Optimized module test timing for fast execution (under 5 seconds each)
- Fixed MLOps test reliability and reduced timing parameters across modules
- Exported all modules (compression, kernels, benchmarking, mlops) to tinytorch package
2025-07-14 23:37:50 -04:00
