From dc8e27abe83e9f1d7e2bbaaa4413fe399caed504 Mon Sep 17 00:00:00 2001 From: Israel Figueroa Date: Tue, 18 Mar 2025 01:30:46 -0300 Subject: [PATCH] simm --- TrainerClass.py | 8 +++++--- train_sequence.py | 4 ++-- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/TrainerClass.py b/TrainerClass.py index 5d3321b..175d345 100644 --- a/TrainerClass.py +++ b/TrainerClass.py @@ -58,6 +58,8 @@ class eNoseTrainer: target_log = '{}/load-{}.log'.format(self.name, self.start) fh = logging.FileHandler(target_log) + optuna.logging.enable_propagation() # Propagate logs to the root logger. + optuna.logging.disable_default_handler() # Stop showing logs in sys.stderr. self.debug = debug @@ -302,7 +304,7 @@ class eNoseTrainer: plt.close() def fit(self): - windows = [64, 128, 256,] + windows = [32, 64, 128,] # windows = [128, 256, 384] total_train_queue = 2*int(1/self.ratio)*(len(self.get_model_train())+len(windows)) self.logger.info("{:=^60}".format(f'Begin Fit {total_train_queue} Models')) @@ -473,7 +475,7 @@ class eNoseTrainer: self.logger.debug(f"Y_train_sample: {Y_train_sample.shape}") self.logger.debug(f"Y_test_sample: {Y_test_sample.shape}") - best_model, study, best_batch_size = self.search_best_conv1D_v1(X_train_sample, X_test_sample, Y_train_sample, Y_test_sample, epochs=10, num_trials=32) + best_model, study, best_batch_size = self.search_best_conv1D_v1(X_train_sample, X_test_sample, Y_train_sample, Y_test_sample, epochs=10, num_trials=10) # Save study results to an Excel file trials_data = [] for trial in study.trials: @@ -560,7 +562,7 @@ class eNoseTrainer: self.logger.debug(f"Y_train_sample: {Y_train_sample.shape}") self.logger.debug(f"Y_test_sample: {Y_test_sample.shape}") - best_model, study, best_batch_size = self.search_best_conv1D_v1(X_train_sample, X_test_sample, Y_train_sample, Y_test_sample, epochs=10, num_trials=32) + best_model, study, best_batch_size = self.search_best_conv1D_v1(X_train_sample, X_test_sample, Y_train_sample, Y_test_sample, epochs=10, num_trials=10) # Save study results to an Excel file trials_data = [] for trial in study.trials: diff --git a/train_sequence.py b/train_sequence.py index 47fa6f0..b89a74b 100644 --- a/train_sequence.py +++ b/train_sequence.py @@ -12,6 +12,8 @@ eNose = eNoseTrainer(eNoseLoader, test_size=0.2, debug=False) eNoseLoader.target_list=['H2',] eNose.fit() +eNoseLoader.target_list=['H2', 'C2H2', 'CH4', 'C2H4', 'C2H6',] +eNose.fit() eNoseLoader.target_list=['C2H2',] eNose.fit() eNoseLoader.target_list=['CH4',] @@ -20,8 +22,6 @@ eNoseLoader.target_list=['C2H4',] eNose.fit() eNoseLoader.target_list=['C2H6',] eNose.fit() -eNoseLoader.target_list=['H2', 'C2H2', 'CH4', 'C2H4', 'C2H6',] -eNose.fit() eNose.wrap_and_save() # eNoseLoader.target_list=['H2',]