fix outputs save path

Author: adelmemariani

dicee/scripts/bayesian_optimization.py

@@ -6,22 +6,22 @@
 from optuna.visualization import plot_parallel_coordinate, plot_contour, plot_edf, plot_optimization_history
 import os
 
-
 def objective(trial, model, dataset, loss):
+
     parser = argparse.ArgumentParser(add_help=False)
 
     dataset = dataset
     model = model
 
     num_epochs = 1
 
-    embedding_dim = 32  # trial.suggest_categorical("embedding_dim", [32, 64])
-    optimizer = "Adam"  # trial.suggest_categorical("optimizer", ["Adam", "Adopt"])
-    batch_size = 1024  # trial.suggest_categorical("batch_size", [512, 1024])
+    embedding_dim = 32 #trial.suggest_categorical("embedding_dim", [32, 64])
+    optimizer = "Adam" #trial.suggest_categorical("optimizer", ["Adam", "Adopt"])
+    batch_size = 1024 #trial.suggest_categorical("batch_size", [512, 1024])
     learning_rate = trial.suggest_float("learning_rate", 0.01, 0.1)
 
-    label_relaxation_alpha = trial.suggest_float("label_relaxation_alpha", 0.01, 0.1, ) if loss == "LRLoss" else 0.0
-    label_smoothing_rate = trial.suggest_float("label_smoothing_rate", 0.01, 0.1) if loss == "LS" else 0.0
+    label_relaxation_alpha = trial.suggest_float("label_relaxation_alpha", 0.01, 0.1,) if loss == "LRLoss" else 0.0
+    label_smoothing_rate = trial.suggest_float("label_smoothing_rate", 0.01, 0.1)  if loss == "LS" else 0.0
 
     parser.add_argument('--loss_fn', type=str, default=loss)
     parser.add_argument("--label_smoothing_rate", type=float, default=label_smoothing_rate)
@@ -69,7 +69,6 @@ def objective(trial, model, dataset, loss):
 
     return result["Test"]["MRR"]
 
-
 # set according to your environment TODO: make it as a parameter
 main_math = "../../../KGs/Datasets_Perturbed/"
 report_folder_name = "./bo_outputs/"
@@ -93,17 +92,15 @@ def objective(trial, model, dataset, loss):
 
             best_trial = study.best_trial
 
-            """
             fig1 = plot_parallel_coordinate(study)
-            fig1.write_image(report_folder_name + f"parallel_coordinate-{dataset}-{model}-{loss}" + ".png")
+            fig1.write_image(report_folder_name + f"parallel_coordinate-{dataset}-{model}-{loss}"+ ".png")
 
             fig3 = plot_edf(study)
             fig3.write_image(report_folder_name + f"plot_edf-{dataset}-{model}-{loss}" + ".png")
 
             fig4 = plot_optimization_history(study)
             fig4.write_image(report_folder_name + f"plot_optimization_history-{dataset}-{model}-{loss}" + ".png")
-            """
-
+            
             if loss == "LRLoss":
                 fig2 = plot_contour(study, params=["label_relaxation_alpha", "learning_rate"])
                 fig2.write_image(report_folder_name + f"contour-{dataset}-{model}-{loss}" + ".png")
@@ -112,8 +109,10 @@ def objective(trial, model, dataset, loss):
                 fig2 = plot_contour(study, params=["label_smoothing_rate", "learning_rate"])
                 fig2.write_image(report_folder_name + f"contour-{dataset}-{model}-{loss}" + ".png")
 
+
             os.makedirs(os.path.dirname(report_folder_name), exist_ok=True)
             with open(report_folder_name + report_file_name, "a") as file:
-                file.write(
-                    f"Value: {best_trial.value}, Params: {best_trial.params}, Dataset: {dataset}, Model: {model}, Loss: {loss} \n")
+                file.write(f"Value: {best_trial.value}, Params: {best_trial.params}, Dataset: {dataset}, Model: {model}, Loss: {loss} \n")
+
 
+0