Update train.py

AMAAI-Lab · Nov 2, 2023 · 02332b5 · 02332b5
1 parent 062e499
commit 02332b5
Showing 1 changed file with 2 additions and 34 deletions.
diff --git a/train.py b/train.py
@@ -149,18 +149,12 @@ def main( vm = "" , isPrintArgs = True ):
 
     ##### Not smoothing evaluation loss #####
     eval_loss_func = nn.CrossEntropyLoss(ignore_index=CHORD_PAD)
-    # eval_loss_func_root = nn.CrossEntropyLoss(ignore_index=CHORD_ROOT_PAD)
-    # eval_loss_func_attr = nn.CrossEntropyLoss(ignore_index=CHORD_ATTR_PAD)
 
     ##### SmoothCrossEntropyLoss or CrossEntropyLoss for training #####
     if(args.ce_smoothing is None):
         train_loss_func = eval_loss_func
-        # train_loss_func_root = eval_loss_func_root
-        # train_loss_func_attr = eval_loss_func_attr
     else:
         train_loss_func = SmoothCrossEntropyLoss(args.ce_smoothing, CHORD_SIZE, ignore_index=CHORD_PAD)
-        # train_loss_func_root = SmoothCrossEntropyLoss(args.ce_smoothing, CHORD_ROOT_SIZE, ignore_index=CHORD_ROOT_PAD)
-        # train_loss_func_attr = SmoothCrossEntropyLoss(args.ce_smoothing, CHORD_ATTR_SIZE, ignore_index=CHORD_ATTR_PAD)
 
     eval_loss_emotion_func = nn.BCEWithLogitsLoss()
     train_loss_emotion_func = eval_loss_emotion_func
@@ -172,8 +166,6 @@ def main( vm = "" , isPrintArgs = True ):
     else:
         lr_scheduler = None
 
-    # opt = Adam(model.parameters(), lr=1e-3, weight_decay=1e-5)
-    # lr_scheduler = LambdaLR(opt, lr_stepper.step)
 
     ##### Tracking best evaluation accuracy #####
     best_eval_acc        = 0.0
@@ -208,27 +200,14 @@ def main( vm = "" , isPrintArgs = True ):
             print(SEPERATOR)
             print("Baseline model evaluation (Epoch 0):")
 
-        # Eval v19
-        # train_loss, train_acc = eval_model(model, train_loader, 
-        #                                    train_loss_func, train_loss_func_root, train_loss_func_attr,
-        #                                    isVideo= args.is_video)
-
-        # eval_loss, eval_acc = eval_model(model, val_loader, 
-        #                                  eval_loss_func, eval_loss_func_root, eval_loss_func_attr,
-        #                                  isVideo= args.is_video)
-
-        # Eval
-
         train_metric_dict = eval_model(model, train_loader, 
                                 train_loss_func, train_loss_emotion_func,
                                 isVideo= args.is_video)
 
         train_total_loss = train_metric_dict["avg_total_loss"]
         train_loss_chord = train_metric_dict["avg_loss_chord"]
         train_loss_emotion = train_metric_dict["avg_loss_emotion"]
-        train_acc = train_metric_dict["avg_acc"]
-        train_cor = train_metric_dict["avg_cor"]
-        train_acc_cor = train_metric_dict["avg_acc_cor"]
+
         train_h1 = train_metric_dict["avg_h1"]
         train_h3 = train_metric_dict["avg_h3"]
         train_h5 = train_metric_dict["avg_h5"]
@@ -240,9 +219,7 @@ def main( vm = "" , isPrintArgs = True ):
         eval_total_loss = eval_metric_dict["avg_total_loss"]
         eval_loss_chord = eval_metric_dict["avg_loss_chord"]
         eval_loss_emotion = eval_metric_dict["avg_loss_emotion"]
-        eval_acc = eval_metric_dict["avg_acc"]
-        eval_cor = eval_metric_dict["avg_cor"]
-        eval_acc_cor = eval_metric_dict["avg_acc_cor"]
+
         eval_h1 = eval_metric_dict["avg_h1"]
         eval_h3 = eval_metric_dict["avg_h3"]
         eval_h5 = eval_metric_dict["avg_h5"]
@@ -254,23 +231,14 @@ def main( vm = "" , isPrintArgs = True ):
         print("Avg train loss (total):", train_total_loss)
         print("Avg train loss (chord):", train_loss_chord)
         print("Avg train loss (emotion):", train_loss_emotion)
-
-        print("Avg train acc:", train_acc)
-        print("Avg train cor:", train_cor)
-        print("Avg train acc_cor:", train_acc_cor)
 
         print("Avg train h1:", train_h1)
         print("Avg train h3:", train_h3)
         print("Avg train h5:", train_h5)
 
-
         print("Avg val loss (total):", eval_total_loss)
         print("Avg val loss (chord):", eval_loss_chord)
         print("Avg val loss (emotion):", eval_loss_emotion)
-
-        print("Avg val acc:", eval_acc)
-        print("Avg val cor:", eval_cor)
-        print("Avg val acc_cor:", eval_acc_cor)
 
         print("Avg val h1:", eval_h1)
         print("Avg val h3:", eval_h3)