Upload tokenizer

special_tokens_map.json

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+{
+  "bos_token": "[BOS]",
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenization_caduceus.py

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+"""Character tokenizer for Hugging Face.
+
+"""
+
+from typing import List, Optional, Dict, Sequence, Tuple
+
+from transformers import PreTrainedTokenizer
+
+
+class CaduceusTokenizer(PreTrainedTokenizer):
+    model_input_names = ["input_ids"]
+
+    def __init__(self,
+                 model_max_length: int,
+                 characters: Sequence[str] = ("A", "C", "G", "T", "N"),
+                 complement_map=None,
+                 bos_token="[BOS]",
+                 eos_token="[SEP]",
+                 sep_token="[SEP]",
+                 cls_token="[CLS]",
+                 pad_token="[PAD]",
+                 mask_token="[MASK]",
+                 unk_token="[UNK]",
+                 **kwargs):
+        """Character tokenizer for Hugging Face transformers.
+
+        Adapted from https://huggingface.co/LongSafari/hyenadna-tiny-1k-seqlen-hf/blob/main/tokenization_hyena.py
+        Args:
+            model_max_length (int): Model maximum sequence length.
+            characters (Sequence[str]): List of desired characters. Any character which
+                is not included in this list will be replaced by a special token called
+                [UNK] with id=6. Following is a list of the special tokens with
+                their corresponding ids:
+                    "[CLS]": 0
+                    "[SEP]": 1
+                    "[BOS]": 2
+                    "[MASK]": 3
+                    "[PAD]": 4
+                    "[RESERVED]": 5
+                    "[UNK]": 6
+                an id (starting at 7) will be assigned to each character.
+            complement_map (Optional[Dict[str, str]]): Dictionary with string complements for each character.
+        """
+        if complement_map is None:
+            complement_map = {"A": "T", "C": "G", "G": "C", "T": "A"}
+        self.characters = characters
+        self.model_max_length = model_max_length
+
+        self._vocab_str_to_int = {
+            "[CLS]": 0,
+            "[SEP]": 1,
+            "[BOS]": 2,
+            "[MASK]": 3,
+            "[PAD]": 4,
+            "[RESERVED]": 5,
+            "[UNK]": 6,
+            **{ch: i + 7 for i, ch in enumerate(self.characters)},
+        }
+        self._vocab_int_to_str = {v: k for k, v in self._vocab_str_to_int.items()}
+        add_prefix_space = kwargs.pop("add_prefix_space", False)
+        padding_side = kwargs.pop("padding_side", "left")
+
+        self._complement_map = {}
+        for k, v in self._vocab_str_to_int.items():
+            complement_id = self._vocab_str_to_int[complement_map[k]] if k in complement_map.keys() else v
+            self._complement_map[self._vocab_str_to_int[k]] = complement_id
+
+        super().__init__(
+            bos_token=bos_token,
+            eos_token=eos_token,
+            sep_token=sep_token,
+            cls_token=cls_token,
+            pad_token=pad_token,
+            mask_token=mask_token,
+            unk_token=unk_token,
+            add_prefix_space=add_prefix_space,
+            model_max_length=model_max_length,
+            padding_side=padding_side,
+            **kwargs,
+        )
+
+    @property
+    def vocab_size(self) -> int:
+        return len(self._vocab_str_to_int)
+
+    @property
+    def complement_map(self) -> Dict[int, int]:
+        return self._complement_map
+
+    def _tokenize(self, text: str, **kwargs) -> List[str]:
+        return list(text.upper())  # Convert all base pairs to uppercase
+
+    def _convert_token_to_id(self, token: str) -> int:
+        return self._vocab_str_to_int.get(token, self._vocab_str_to_int["[UNK]"])
+
+    def _convert_id_to_token(self, index: int) -> str:
+        return self._vocab_int_to_str[index]
+
+    def convert_tokens_to_string(self, tokens):
+        return "".join(tokens)  # Note: this operation has lost info about which base pairs were originally lowercase
+
+    def get_special_tokens_mask(
+        self,
+        token_ids_0: List[int],
+        token_ids_1: Optional[List[int]] = None,
+        already_has_special_tokens: bool = False,
+    ) -> List[int]:
+        if already_has_special_tokens:
+            return super().get_special_tokens_mask(
+                token_ids_0=token_ids_0,
+                token_ids_1=token_ids_1,
+                already_has_special_tokens=True,
+            )
+
+        result = ([0] * len(token_ids_0)) + [1]
+        if token_ids_1 is not None:
+            result += ([0] * len(token_ids_1)) + [1]
+        return result
+
+    def build_inputs_with_special_tokens(
+        self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None
+    ) -> List[int]:
+        sep = [self.sep_token_id]
+        # cls = [self.cls_token_id]
+        result = token_ids_0 + sep
+        if token_ids_1 is not None:
+            result += token_ids_1 + sep
+        return result
+
+    def get_vocab(self) -> Dict[str, int]:
+        return self._vocab_str_to_int
+
+    # Fixed vocabulary with no vocab file
+    def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> Tuple:
+        return ()

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[BOS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "6": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "auto_map": {
+    "AutoTokenizer": [
+      "tokenization_caduceus.CaduceusTokenizer",
+      null
+    ]
+  },
+  "bos_token": "[BOS]",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "padding_side": "left",
+  "sep_token": "[SEP]",
+  "tokenizer_class": "CaduceusTokenizer",
+  "unk_token": "[UNK]"
+}