diff --git a/optimization_log_20250928_214329.txt b/optimization_log_20250928_214329.txt index 7f056b38..7ef5d1e5 100644 --- a/optimization_log_20250928_214329.txt +++ b/optimization_log_20250928_214329.txt @@ -114,3 +114,23 @@ Testing Optimization Level 18: Caching [2025-09-28 21:47:18] ✅ Complete in 1.88s [2025-09-28 21:47:18] Committing results for Caching... +[2025-09-28 21:47:18] Committed results +[2025-09-28 21:47:18] +Verifying previous optimizations still work... +[2025-09-28 21:47:18] Previous optimizations verified +[2025-09-28 21:47:18] +Testing Optimization Level 19: Benchmarking +[2025-09-28 21:47:18] Description: Module 19: Advanced benchmarking suite +[2025-09-28 21:47:18] ------------------------------------------------------------ +[2025-09-28 21:47:18] Testing Perceptron with Benchmarking... +[2025-09-28 21:47:20] ✅ Complete in 1.87s +[2025-09-28 21:47:20] Testing XOR with Benchmarking... +[2025-09-28 21:47:22] ✅ Complete in 1.92s +[2025-09-28 21:47:22] Testing MNIST with Benchmarking... +[2025-09-28 21:47:24] ✅ Complete in 2.04s +[2025-09-28 21:47:24] Testing CIFAR with Benchmarking... +[2025-09-28 21:47:54] ⏱️ Timeout after 60s +[2025-09-28 21:47:54] Testing TinyGPT with Benchmarking... +[2025-09-28 21:47:56] ✅ Complete in 1.88s +[2025-09-28 21:47:56] +Committing results for Benchmarking... diff --git a/results_Benchmarking.json b/results_Benchmarking.json new file mode 100644 index 00000000..8b6ed4ef --- /dev/null +++ b/results_Benchmarking.json @@ -0,0 +1,34 @@ +{ + "Perceptron": { + "success": true, + "time": 1.8683466911315918, + "output_preview": "ion\n\n\ud83d\ude80 Next Steps:\n \u2022 Continue to XOR 1969 milestone after Module 06 (Autograd)\n \u2022 YOUR foundation enables solving non-linear problems!\n \u2022 With 100.0% accuracy, YOUR perceptron works perfectly!\n", + "loss": 0.2038, + "accuracy": 100.0 + }, + "XOR": { + "success": true, + "time": 1.9171321392059326, + "output_preview": "ayer networks\n\n\ud83d\ude80 Next Steps:\n \u2022 Continue to MNIST MLP after Module 08 (Training)\n \u2022 YOUR XOR solution scales to real vision problems!\n \u2022 Hidden layers principle powers all modern deep learning!\n", + "loss": 0.2497, + "accuracy": 54.5 + }, + "MNIST": { + "success": true, + "time": 2.0394182205200195, + "output_preview": " a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n one_hot[i, int(labels_np[i])] = 1.0\n", + "loss": 0.0, + "accuracy": 7.5 + }, + "CIFAR": { + "success": false, + "time": 60, + "timeout": true + }, + "TinyGPT": { + "success": true, + "time": 1.876978874206543, + "output_preview": "ining\n \u2022 Complete transformer architecture from first principles\n\n\ud83c\udfed Production Note:\n Real PyTorch uses optimized CUDA kernels for attention,\n but you built and understand the core mathematics!\n", + "loss": 0.3195 + } +} \ No newline at end of file