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1aea4b3aba
New Features: - Add MSEBackward gradient computation for regression tasks - Patch MSELoss in enable_autograd() for gradient tracking - All 3 loss functions now support autograd: MSE, BCE, CrossEntropy Test Suite Organization: - Reorganize tests/ into focused directories - Create tests/integration/ for cross-module tests - Create tests/05_autograd/ for autograd edge cases - Create tests/debugging/ for common student pitfalls - Add comprehensive tests/README.md explaining test philosophy Integration Tests: - Move test_gradient_flow.py to integration/ - 20 comprehensive gradient flow tests - Tests cover: tensors, layers, activations, losses, optimizers - Tests validate: basic ops, chain rule, broadcasting, training loops - 19/20 tests passing (MSE now fixed!) Results: ✅ Perceptron learns: 50% → 93% accuracy ✅ Clean test organization guides future development ✅ Tests catch the exact bugs that broke training Pedagogical Value: - Test organization teaches testing best practices - Gradient flow tests show what integration testing catches - Sets foundation for debugging/diagnostic tests
13 lines
478 B
Python
13 lines
478 B
Python
"""
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Debugging tests for common student pitfalls.
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These tests identify and diagnose common issues students encounter:
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- Vanishing gradients (ReLU dying, sigmoid saturation)
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- Exploding gradients (unstable initialization)
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- Silent failures (forgot backward(), forgot zero_grad())
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- Common mistakes (wrong loss function, learning rate issues)
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Goal: When a test fails, the error message should guide students
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to the solution. These are pedagogical tests that teach debugging.
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"""
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