diff --git a/optimization_log_20250928_214329.txt b/optimization_log_20250928_214329.txt index 28858638..af517871 100644 --- a/optimization_log_20250928_214329.txt +++ b/optimization_log_20250928_214329.txt @@ -54,3 +54,23 @@ Testing Optimization Level 15: Acceleration [2025-09-28 21:45:23] ✅ Complete in 1.87s [2025-09-28 21:45:23] Committing results for Acceleration... +[2025-09-28 21:45:24] Committed results +[2025-09-28 21:45:24] +Verifying previous optimizations still work... +[2025-09-28 21:45:24] Previous optimizations verified +[2025-09-28 21:45:24] +Testing Optimization Level 16: Quantization +[2025-09-28 21:45:24] Description: Module 16: Quantization and compression +[2025-09-28 21:45:24] ------------------------------------------------------------ +[2025-09-28 21:45:24] Testing Perceptron with Quantization... +[2025-09-28 21:45:26] ✅ Complete in 1.86s +[2025-09-28 21:45:26] Testing XOR with Quantization... +[2025-09-28 21:45:27] ✅ Complete in 1.90s +[2025-09-28 21:45:27] Testing MNIST with Quantization... +[2025-09-28 21:45:29] ✅ Complete in 2.05s +[2025-09-28 21:45:29] Testing CIFAR with Quantization... +[2025-09-28 21:46:00] ⏱️ Timeout after 60s +[2025-09-28 21:46:00] Testing TinyGPT with Quantization... +[2025-09-28 21:46:01] ✅ Complete in 1.84s +[2025-09-28 21:46:01] +Committing results for Quantization... diff --git a/results_Quantization.json b/results_Quantization.json new file mode 100644 index 00000000..7bc1eb26 --- /dev/null +++ b/results_Quantization.json @@ -0,0 +1,34 @@ +{ + "Perceptron": { + "success": true, + "time": 1.8575267791748047, + "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": 1.8962900638580322, + "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": 2.04866886138916, + "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": 10.0 + }, + "CIFAR": { + "success": false, + "time": 60, + "timeout": true + }, + "TinyGPT": { + "success": true, + "time": 1.8439507484436035, + "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": 0.3174 + } +} \ No newline at end of file