3 Commits

Author	SHA1	Message	Date
Vijay Janapa Reddi	90581b23c0	Update test suite for module restructuring ... Updated test imports and paths after modules/source/ removal: - Progressive integration tests for modules 03, 06, 08, 13, 14 - Checkpoint integration tests - Module completion orchestrator - Optimizer integration tests - Gradient flow regression tests Updated test documentation: - tests/README.md with new module paths - tests/TEST_STRATEGY.md with restructuring notes All tests now reference modules/XX_name/ instead of modules/source/.	2025-11-10 19:42:23 -05:00
Vijay Janapa Reddi	39dc0bd2a6	test: Move gradient flow tests to proper locations ... - Deleted root-level tests/test_gradient_flow.py - Comprehensive tests now in tests/regression/test_gradient_flow_fixes.py - Module-specific tests in tests/05_autograd/test_batched_matmul_backward.py - Better test organization following TinyTorch conventions	2025-10-27 22:41:03 -04:00
Vijay Janapa Reddi	e3723dccac	Solve XOR problem - multi-layer networks work! ... Add test_xor_simple.py - validates multi-layer gradient flow - 100% accuracy on XOR (the 1969 'impossible' problem) - Hidden layer (2→4) + ReLU + output (4→1) architecture - Gradients flow correctly through 2 layers - Loss decreases smoothly during training This proves: ✅ Multi-layer networks work ✅ Backprop works through hidden layers ✅ ReLU activation works in training ✅ The 1969 AI Winter problem is solved! Historical significance: Minsky proved single-layer perceptrons couldn't solve XOR. Multi-layer networks (what we built) can!	2025-09-30 14:05:13 -04:00