fix: experiment setting error

Author: Yeongsoo

evaluate_trained_models.sh

@@ -3,24 +3,24 @@
 gpu_id=0 
 nb_worker=24
 
-exp_name="decode_ASC"
-CUDA_VISIBLE_DEVICES=${gpu_id} python evaluate.py -verbose 0 \
+exp_name="EvalASC"
+CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
   -task ASC \
   -name ${exp_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \
   -nb_worker ${nb_worker} \
   -bs_ASC 32 -bs_SED 24 -bs_TAG 32 \
   -dir_model_weight ./weights/DcaseNet_v3_finetune_best_ASC.pt
 
-exp_name="decode_TAG"
-CUDA_VISIBLE_DEVICES=${gpu_id} python evaluate.py -verbose 0 \
+exp_name="EvalTAG"
+CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
   -task TAG \
   -name ${exp_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \
   -nb_worker ${nb_worker} \
   -bs_ASC 32 -bs_SED 24 -bs_TAG 32 \
   -dir_model_weight ./weights/DcaseNet_v3_finetune_best_TAG.pt
 
-exp_name="decode_SED"
-CUDA_VISIBLE_DEVICES=${gpu_id} python evaluate.py -verbose 0 \
+exp_name="EvalSED"
+CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
   -task SED \
   -name ${exp_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \
   -nb_worker ${nb_worker} \

main.py

@@ -164,11 +164,11 @@ def main():
     with open(save_dir+'modelsumm.txt', 'w') as f: f.write(str(model_summ))
 
     #load weights
-    if args.phase == 'fine_tune' or args.phase == 'eval':
+    if 'fine-tune' in args.name or 'Eval' in args.name:
         model.load_state_dict(torch.load(args.dir_model_weight))
     model = model.to(device)
 
-    if args.phase == 'eval':
+    if 'Eval' in args.name:
         if 'ASC' in args.task:
             acc, conf_mat = evaluate_ASC(model = model,
                 evlset_gen = evlset_gen_ASC,

parser.py

@@ -9,7 +9,6 @@ def get_args():
     ##########
     ## PATH ##
     ##########
-    parser.add_argument('-phase', type = str, required = True)
     parser.add_argument('-name', type = str, required = True)
     parser.add_argument('-save_dir', type = str, required = True)
     parser.add_argument('-dir_model_weight', type = str, default = '')

train.sh

@@ -12,7 +12,7 @@ fi
 if [ ${phase} -le 0 ]; then
   ######
   # Joint train ASC, TAG, and SED tasks using DcaseNet-v3 architecture
-  CUDA_VISIBLE_DEVICES=${gpu_id} python joint_train_DcaseNet.py -verbose 0 \
+  CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
     -nb_iter_per_epoch 500 \
     -task ASC SED TAG \
     -name ${joint_model_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \
@@ -28,8 +28,8 @@ fi
 if [ ${phase} -le 1 ]; then
   #####
   # fine-tune for ASC
-  exp_name="finetune_ASC"
-  CUDA_VISIBLE_DEVICES=${gpu_id} python fine_tune_single_task.py -verbose 0 \
+  exp_name="fine-tune_ASC"
+  CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
     -nb_iter_per_epoch 500 \
     -task ASC \
     -name ${exp_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \
@@ -46,8 +46,8 @@ fi
 if [ ${phase} -le 1 ]; then
   #####
   # fine-tune for TAG
-  exp_name="finetune_TAG"
-  CUDA_VISIBLE_DEVICES=${gpu_id} python fine_tune_single_task.py -verbose 0 \
+  exp_name="fine-tune_TAG"
+  CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
     -nb_iter_per_epoch 500 \
     -task TAG \
     -name ${exp_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \
@@ -64,8 +64,8 @@ fi
 if [ ${phase} -le 1 ]; then
   #####
   # fine-tune for SED
-  exp_name="finetune_SED"
-  CUDA_VISIBLE_DEVICES=${gpu_id} python fine_tune_single_task.py -verbose 0 \
+  exp_name="fine-tune_SED"
+  CUDA_VISIBLE_DEVICES=${gpu_id} python main.py -verbose 0 \
     -nb_iter_per_epoch 500 \
     -task TAG \
     -name ${exp_name} -model_scp DcaseNet -model_name get_DcaseNet_v3 \