[`Tokenizer Serialization`] Fix the broken serialisation (#27099)

* nits

* nits

* actual fix

* style

* ze fix

* fix fix fix style

src/transformers/models/pegasus/tokenization_pegasus_fast.py

@@ -145,6 +145,8 @@ class PegasusTokenizerFast(PreTrainedTokenizerFast):
         from_slow = kwargs.pop("from_slow", None)
         from_slow = from_slow or str(pad_token) != "<pad>" or str(eos_token) != "</s>" or str(unk_token) != "<unk>"
 
+        kwargs.pop("added_tokens_decoder", {})
+
         super().__init__(
             vocab_file,
             tokenizer_file=tokenizer_file,

src/transformers/tokenization_utils_base.py

@@ -2235,7 +2235,7 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
 
             # allows converting a fast -> slow: add the `tokenizer.json`'s `"added_tokens"` to the slow tokenizer
             # if `tokenizer_config.json` is `None`
-            if "Fast" not in cls.__name__ and tokenizer_file is not None:
+            if tokenizer_file is not None:
                 # This is for slow so can be done before
                 with open(tokenizer_file, encoding="utf-8") as tokenizer_file_handle:
                     tokenizer_file_handle = json.load(tokenizer_file_handle)
@@ -2247,14 +2247,14 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
             # end legacy
 
         # Passing AddedTokens and not strings to the class to prevent it from casting the string to a different AddedToken
+        # convert {'__type': 'AddedToken', 'content': '<ent>', 'lstrip': False, 'normalized': True, ...} to AddedTokens
+        init_kwargs["added_tokens_decoder"] = added_tokens_decoder
+        init_kwargs = cls.convert_added_tokens(init_kwargs, save=False)
         for key in cls.SPECIAL_TOKENS_ATTRIBUTES & init_kwargs.keys():
             if added_tokens_map != {} and init_kwargs[key] is not None:
                 if key != "additional_special_tokens":
-                    init_kwargs[key] = added_tokens_map.get(init_kwargs[key], init_kwargs[key])
+                    init_kwargs[key] = added_tokens_map.get(str(init_kwargs[key]), init_kwargs[key])
 
-        init_kwargs["added_tokens_decoder"] = added_tokens_decoder
-        # convert {'__type': 'AddedToken', 'content': '<ent>', 'lstrip': False, 'normalized': True, ...} to AddedTokens
-        init_kwargs = cls.convert_added_tokens(init_kwargs, save=False)
         # Instantiate the tokenizer.
         try:
             tokenizer = cls(*init_inputs, **init_kwargs)