fix: Runtime errors

main.py

@@ -22,6 +22,7 @@ def main():
                 data_root = args.data_root,
                 n_trials = 3 if args.debug else None,
                 size = 2**10 if args.debug else None,
+                method = args.method,
                 model_name=args.model,
                 model_path = args.model_load_path,
                 model_out = args.model_save_path
@@ -32,6 +33,8 @@ def main():
 
         case _:
             raise NotImplementedError(f"Mode {args.mode} is not implemented yet")
+    
+    print("Done")
 
 
 if __name__ == "__main__":

src/args.py

@@ -29,18 +29,15 @@ def parse_arguments():
     subparsers = parser.add_subparsers(dest="mode", required=True,
                                        help="Mode to run in")
 
-    # TODO
+    train_parser = subparsers.add_parser("train",
-    fetch_parser = subparsers.add_parser("fetch", parents=[dataparser],
+                                         parents=[dataparser, modelparser],
-                                         help="Only fetch the dataset, then exit")
+                                         help="Do a full training")
-
+    train_parser.add_argument("--method",
-    train_parser = subparsers.add_parser("train", parents=[dataparser, modelparser])
+                              choices=["fetch", "optuna", "full"], required=True,
-    train_parser.add_argument("--method", choices=["optuna", "full"], required=True,
                               help="Method to use for training")
 
-    # TODO
     compress_parser = subparsers.add_parser("compress", parents=[modelparser, fileparser])
 
-    # TODO
     decompress_parser = subparsers.add_parser("decompress", parents=[modelparser, fileparser])
 
     return parser.parse_args(), parser.print_help

src/process.py

@@ -2,8 +2,12 @@ import torch
 
 
 def compress(
-        input_file: str | None = None
+    device,
+    model_path: str,
+    output_file: str,
+    input_file: str | None = None
 ):
+    # Get input to compress
     if input_file:
         with open(input_file, "rb") as file:
             byte_data = file.read()
@@ -15,6 +19,9 @@ def compress(
     tensor = torch.tensor(list(byte_data), dtype=torch.long)
     print(tensor)
 
+    # Get model
+    model = torch.load(model_path, weights_only=False)
+
     # TODO Feed to model for compression, store result
     return
 

src/train.py

@@ -15,7 +15,6 @@ def train(
         data_root: str,
         n_trials: int | None = None,
         size: int | None = None,
-        mode: str = "train",
         method: str = 'optuna',
         model_name: str | None = None,
         model_path: str | None = None,
@@ -30,7 +29,7 @@ def train(
         model = model_called[model_name]
     else:
         print("Loading model from disk")
-        model = torch.load(model_path)
+        model = torch.load(model_path, weights_only=False)
 
     dataset_common_args = {
         'root': data_root,
@@ -48,7 +47,7 @@ def train(
         # TODO Allow to import arbitrary files
         raise NotImplementedError(f"Importing external datasets is not implemented yet")
 
-    if mode == 'fetch':
+    if method == 'fetch':
         # TODO More to earlier in chain, because now everything is converted into tensors as well?
         exit(0)
 
@@ -72,3 +71,5 @@ def train(
     # Make sure path exists
     Path(f).parent.mkdir(parents=True, exist_ok=True)
     torch.save(best_model, f)
+    print(f"Saved model to '{f}'")
+