2025-03-29 16:23:07,752 - INFO - Starting EvoNet Pipeline Run: 20250329_162307
2025-03-29 16:23:07,752 - INFO - Output directory: ./my_neuroevolution_results\evorun_20250329_162307
2025-03-29 16:23:07,752 - INFO - Configuration:
2025-03-29 16:23:07,752 - INFO -   output_base_dir: ./my_neuroevolution_results
2025-03-29 16:23:07,752 - INFO -   seq_length: 10
2025-03-29 16:23:07,752 - INFO -   train_samples: 5000
2025-03-29 16:23:07,752 - INFO -   test_samples: 1000
2025-03-29 16:23:07,753 - INFO -   pop_size: 80
2025-03-29 16:23:07,753 - INFO -   generations: 100
2025-03-29 16:23:07,753 - INFO -   mutation_rate: 0.5
2025-03-29 16:23:07,753 - INFO -   weight_mut_rate: 0.8
2025-03-29 16:23:07,753 - INFO -   activation_mut_rate: 0.2
2025-03-29 16:23:07,753 - INFO -   mutation_strength: 0.1
2025-03-29 16:23:07,753 - INFO -   tournament_size: 5
2025-03-29 16:23:07,753 - INFO -   elitism_count: 2
2025-03-29 16:23:07,753 - INFO -   batch_size: 64
2025-03-29 16:23:07,753 - INFO -   epochs_final_train: 100
2025-03-29 16:23:07,753 - INFO -   seed: 123
2025-03-29 16:23:07,754 - INFO - Configuration saved to ./my_neuroevolution_results\evorun_20250329_162307\config.json
2025-03-29 16:23:07,755 - INFO - Using random seed: 123
2025-03-29 16:23:07,766 - WARNING - GPU not found. Using CPU.
2025-03-29 16:23:07,766 - INFO - Generating 5000 samples with sequence length 10...
2025-03-29 16:23:07,768 - INFO - Data generation complete.
2025-03-29 16:23:07,768 - INFO - Generating 1000 samples with sequence length 10...
2025-03-29 16:23:07,768 - INFO - Data generation complete.
2025-03-29 16:23:07,769 - INFO - Initializing population of 80 individuals...
2025-03-29 16:23:09,618 - INFO - Population initialized.
2025-03-29 16:23:09,619 - INFO - Starting evolution for 100 generations...
2025-03-29 16:23:09,815 - WARNING - 5 out of the last 5 calls to <function get_predictions at 0x0000029FA1CB5090> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.
2025-03-29 16:23:09,837 - WARNING - 6 out of the last 6 calls to <function get_predictions at 0x0000029FA1CB5090> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.
2025-03-29 16:23:11,240 - INFO - Generation 1: New overall best fitness: 0.0005
2025-03-29 16:23:11,241 - INFO - Generation 1/100 - Best Fitness: 0.0005, Avg Fitness: 0.0003
2025-03-29 16:23:15,416 - INFO - Generation 2: New overall best fitness: 0.0005
2025-03-29 16:23:15,416 - INFO - Generation 2/100 - Best Fitness: 0.0005, Avg Fitness: 0.0003
2025-03-29 16:23:19,031 - INFO - Generation 3: New overall best fitness: 0.0006
2025-03-29 16:23:19,032 - INFO - Generation 3/100 - Best Fitness: 0.0006, Avg Fitness: 0.0003
2025-03-29 16:23:22,543 - INFO - Generation 4: New overall best fitness: 0.0007
2025-03-29 16:23:22,544 - INFO - Generation 4/100 - Best Fitness: 0.0007, Avg Fitness: 0.0004
2025-03-29 16:23:26,214 - INFO - Generation 5: New overall best fitness: 0.0007
2025-03-29 16:23:26,214 - INFO - Generation 5/100 - Best Fitness: 0.0007, Avg Fitness: 0.0005
2025-03-29 16:23:31,401 - INFO - Generation 6: New overall best fitness: 0.0007
2025-03-29 16:23:31,402 - INFO - Generation 6/100 - Best Fitness: 0.0007, Avg Fitness: 0.0005
2025-03-29 16:23:36,194 - INFO - Generation 7/100 - Best Fitness: 0.0007, Avg Fitness: 0.0006
2025-03-29 16:23:40,653 - INFO - Generation 8/100 - Best Fitness: 0.0007, Avg Fitness: 0.0006
2025-03-29 16:23:45,833 - INFO - Generation 9: New overall best fitness: 0.0009
2025-03-29 16:23:45,834 - INFO - Generation 9/100 - Best Fitness: 0.0009, Avg Fitness: 0.0006
2025-03-29 16:23:51,287 - INFO - Generation 10/100 - Best Fitness: 0.0009, Avg Fitness: 0.0006
2025-03-29 16:23:57,811 - INFO - Generation 11: New overall best fitness: 0.0010
2025-03-29 16:23:57,812 - INFO - Generation 11/100 - Best Fitness: 0.0010, Avg Fitness: 0.0006
2025-03-29 16:24:03,660 - INFO - Generation 12/100 - Best Fitness: 0.0010, Avg Fitness: 0.0007
2025-03-29 16:24:08,561 - INFO - Generation 13/100 - Best Fitness: 0.0010, Avg Fitness: 0.0007
2025-03-29 16:24:13,156 - INFO - Generation 14/100 - Best Fitness: 0.0010, Avg Fitness: 0.0007
2025-03-29 16:24:18,199 - INFO - Generation 15/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:24:23,022 - INFO - Generation 16/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:24:27,709 - INFO - Generation 17/100 - Best Fitness: 0.0010, Avg Fitness: 0.0009
2025-03-29 16:24:32,992 - INFO - Generation 18/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:24:38,218 - INFO - Generation 19/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:24:43,234 - INFO - Generation 20/100 - Best Fitness: 0.0010, Avg Fitness: 0.0007
2025-03-29 16:24:48,349 - INFO - Generation 21/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:24:53,961 - INFO - Generation 22/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:24:59,377 - INFO - Generation 23/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:25:05,294 - INFO - Generation 24/100 - Best Fitness: 0.0010, Avg Fitness: 0.0008
2025-03-29 16:25:11,954 - INFO - Generation 25: New overall best fitness: 0.0011
2025-03-29 16:25:11,954 - INFO - Generation 25/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:18,394 - INFO - Generation 26/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:24,756 - INFO - Generation 27/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:30,985 - INFO - Generation 28/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:37,146 - INFO - Generation 29/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:42,858 - INFO - Generation 30/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:48,828 - INFO - Generation 31/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:25:54,665 - INFO - Generation 32/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:26:01,264 - INFO - Generation 33/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:26:07,385 - INFO - Generation 34/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:26:13,600 - INFO - Generation 35/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:26:20,388 - INFO - Generation 36/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:26:27,847 - INFO - Generation 37/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:26:34,794 - INFO - Generation 38/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:26:41,511 - INFO - Generation 39/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:26:48,222 - INFO - Generation 40/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:26:55,038 - INFO - Generation 41/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:03,038 - INFO - Generation 42/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:10,563 - INFO - Generation 43/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:18,195 - INFO - Generation 44/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:26,225 - INFO - Generation 45/100 - Best Fitness: 0.0011, Avg Fitness: 0.0007
2025-03-29 16:27:33,738 - INFO - Generation 46/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:41,358 - INFO - Generation 47/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:48,662 - INFO - Generation 48/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:27:57,800 - INFO - Generation 49/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:28:05,729 - INFO - Generation 50/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:28:13,621 - INFO - Generation 51/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:28:22,441 - INFO - Generation 52/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:28:30,788 - INFO - Generation 53/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:28:39,245 - INFO - Generation 54/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:28:48,128 - INFO - Generation 55/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:28:56,611 - INFO - Generation 56/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:29:07,827 - INFO - Generation 57/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:29:17,239 - INFO - Generation 58/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:29:28,206 - INFO - Generation 59/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:29:37,831 - INFO - Generation 60/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:29:46,407 - INFO - Generation 61/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:29:55,415 - INFO - Generation 62/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:30:05,102 - INFO - Generation 63/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:30:14,019 - INFO - Generation 64/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:30:23,684 - INFO - Generation 65/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:30:33,262 - INFO - Generation 66/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:30:42,568 - INFO - Generation 67/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:30:53,168 - INFO - Generation 68/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:31:04,197 - INFO - Generation 69/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:31:17,892 - INFO - Generation 70/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:31:30,381 - INFO - Generation 71/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:31:42,523 - INFO - Generation 72/100 - Best Fitness: 0.0011, Avg Fitness: 0.0007
2025-03-29 16:31:54,222 - INFO - Generation 73/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:32:05,454 - INFO - Generation 74/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:32:16,454 - INFO - Generation 75/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:32:28,258 - INFO - Generation 76/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:32:39,477 - INFO - Generation 77/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:32:50,192 - INFO - Generation 78/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:33:01,331 - INFO - Generation 79/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:33:13,647 - INFO - Generation 80/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:33:27,063 - INFO - Generation 81/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:33:40,751 - INFO - Generation 82/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:33:53,452 - INFO - Generation 83/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:34:08,825 - INFO - Generation 84/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:34:20,926 - INFO - Generation 85/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:34:32,460 - INFO - Generation 86/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:34:44,641 - INFO - Generation 87/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:34:56,168 - INFO - Generation 88/100 - Best Fitness: 0.0011, Avg Fitness: 0.0007
2025-03-29 16:35:08,763 - INFO - Generation 89/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:35:20,565 - INFO - Generation 90/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:35:33,487 - INFO - Generation 91/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:35:49,718 - INFO - Generation 92/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:36:05,621 - INFO - Generation 93/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:36:19,000 - INFO - Generation 94/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:36:31,437 - INFO - Generation 95/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:36:44,000 - INFO - Generation 96/100 - Best Fitness: 0.0011, Avg Fitness: 0.0008
2025-03-29 16:36:56,637 - INFO - Generation 97/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:37:10,609 - INFO - Generation 98/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:37:25,139 - INFO - Generation 99/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:37:43,057 - INFO - Generation 100/100 - Best Fitness: 0.0011, Avg Fitness: 0.0009
2025-03-29 16:37:45,655 - INFO - Evolution complete.
2025-03-29 16:37:45,659 - INFO - Fitness history data saved to ./my_neuroevolution_results\evorun_20250329_162307\fitness_history.csv
2025-03-29 16:37:47,223 - INFO - Fitness history plot saved to ./my_neuroevolution_results\evorun_20250329_162307\fitness_history.png
2025-03-29 16:37:47,223 - INFO - Starting final training of the best evolved model...
2025-03-29 16:37:59,419 - INFO - Final training complete.
2025-03-29 16:37:59,419 - INFO - Evaluating final model on test data...
2025-03-29 16:37:59,569 - INFO - Final Test MSE: 38.610789
2025-03-29 16:37:59,585 - INFO - Average Kendall's Tau (on 100 samples): 0.9964
2025-03-29 16:37:59,630 - INFO - Final trained model saved to ./my_neuroevolution_results\evorun_20250329_162307\best_evolved_model_trained.keras
2025-03-29 16:37:59,635 - INFO - Final results saved to ./my_neuroevolution_results\evorun_20250329_162307\final_results.json
2025-03-29 16:37:59,635 - INFO - Pipeline finished successfully!