backup

configs/default.yaml

@@ -1,6 +1,6 @@
 Data:
-  preprocess_root: "../data/processed_dataset/DatasetJSON/"
-  train_vocab_file: "../data/processed_dataset/train_external_function_name_vocab.jsonl"
+  preprocess_root: "/root/autodl-tmp/"
+  train_vocab_file: "/root/autodl-tmp/train_external_function_name_vocab.jsonl"
   max_vocab_size: 10000         # modify according to the result of 1BuildExternalVocab.py
 Training:
   cuda: True                    # enable GPU training if cuda is available

src/DistTrainModel.py

@@ -265,7 +265,7 @@ def main_train_worker(local_rank: int, nprocs: int, train_params: TrainParams, m
 
 
 # https://hydra.cc/docs/tutorials/basic/your_first_app/defaults#overriding-a-config-group-default
-@hydra.main(config_path="../configs/", config_name="default.yaml")
+@hydra.main(config_path="../configs/", config_name="default.yaml", version_base=None)
 def main_app(config: DictConfig):
     # set seed for determinism for reproduction
     random.seed(config.Training.seed)

src/utils/PreProcessedDataset.py

@@ -23,12 +23,15 @@ class MalwareDetectionDataset(Dataset):
             if os.path.splitext(name)[-1] == '.pt':
                 files.append(name)
         return files
-    
+
     def __len__(self):
         # def len(self):
         # return 201
         return len(self.malware_files) + len(self.benign_files)
-    
+
+    def len(self):
+        return len(self.malware_files) + len(self.benign_files)
+
     def get(self, idx):
         split = len(self.malware_files)
         # split = 100