Fix deprecated argument transformers

.gitignore

@@ -1,2 +1,5 @@
 __pycache__
-*~
+*~
+
+# PyCharm folders
+/.idea

diaparser/cmds/biaffine_dependency.py

@@ -21,6 +21,7 @@ def main():
     subparser.add_argument('--punct', action='store_true', help='whether to include punctuation')
     subparser.add_argument('--max-len', type=int, help='max length of the sentences')
     subparser.add_argument('--buckets', default=32, type=int, help='max num of buckets to use')
+    subparser.add_argument("--epochs", default=5000, type=int, help="Number of epochs to be run during training.")
     subparser.add_argument('--train', required=True, help='path to train file')
     subparser.add_argument('--dev', required=True, help='path to dev file')
     subparser.add_argument('--test', help='path to test file')

diaparser/modules/lstm.py

@@ -83,8 +83,10 @@ def reset_parameters(self):
     def permute_hidden(self, hx, permutation):
         if permutation is None:
             return hx
-        h = apply_permutation(hx[0], permutation)
-        c = apply_permutation(hx[1], permutation)
+        """h = apply_permutation(hx[0], permutation)
+        c = apply_permutation(hx[1], permutation)"""
+        h = hx[0].index_select(1, permutation)
+        c = hx[1].index_select(1, permutation)
 
         return h, c
 

diaparser/parsers/biaffine_dependency.py

@@ -243,7 +243,7 @@ def build(cls, path, min_freq=2, fix_len=20, **kwargs):
         elif args.feat == 'bert':
             tokenizer = BertField.tokenizer(args.bert)
 
-            args.max_len = min(args.max_len or tokenizer.max_len, tokenizer.max_len)
+            args.max_len = min(args.max_len or tokenizer.model_max_length, tokenizer.model_max_length)
             FEAT = BertField('bert', tokenizer, fix_len=args.fix_len)
             WORD.bos = FEAT.bos  # ensure representations have the same length
         else:

diaparser/parsers/parser.py

@@ -248,7 +248,7 @@ def load(cls, name_or_path='', lang='en', cache_dir=os.path.expanduser('~/.cache
         args.device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
         if os.path.exists(name_or_path):
-            state = torch.load(name_or_path)
+            state = torch.load(name_or_path, weights_only=False)
         else:
             url = select(name=name_or_path, lang=lang, **kwargs)
             if url is None: