import os from shutil import copyfile from typing import Optional, Tuple from tokenizers import processors from transformers.tokenization_utils_fast import PreTrainedTokenizerFast from transformers.utils import is_sentencepiece_available, logging from transformers.utils.versions import require_version require_version("tokenizers>=0.13.3") logger = logging.get_logger(__name__) VOCAB_FILES_NAMES = {"vocab_file": "tokenizer.model", "tokenizer_file": "tokenizer.json"} # fmt: off DEFAULT_SYSTEM_PROMPT = """You are CrystalCoder, a helpful and intelligent assistant. Follow the instructions and answer the questions as accurately as possible.""" # fmt: on class CrystalCoderTokenizerFast(PreTrainedTokenizerFast): vocab_files_names = VOCAB_FILES_NAMES slow_tokenizer_class = None padding_side = "left" model_input_names = ["input_ids", "attention_mask"] def __init__( self, vocab_file=None, tokenizer_file=None, clean_up_tokenization_spaces=False, unk_token="<|unk|>", bos_token="<|startoftext|>", eos_token="<|endoftext|>", add_bos_token=False, add_eos_token=False, use_default_system_prompt=False, **kwargs, ): super().__init__( vocab_file=vocab_file, tokenizer_file=tokenizer_file, clean_up_tokenization_spaces=clean_up_tokenization_spaces, unk_token=unk_token, bos_token=bos_token, eos_token=eos_token, use_default_system_prompt=use_default_system_prompt, **kwargs, ) self._add_bos_token = add_bos_token self._add_eos_token = add_eos_token self.update_post_processor() self.use_default_system_prompt = use_default_system_prompt self.vocab_file = vocab_file @property def can_save_slow_tokenizer(self) -> bool: return os.path.isfile(self.vocab_file) if self.vocab_file else False def update_post_processor(self): """ Updates the underlying post processor with the current `bos_token` and `eos_token`. """ bos = self.bos_token bos_token_id = self.bos_token_id if bos is None and self.add_bos_token: raise ValueError("add_bos_token = True but bos_token = None") eos = self.eos_token eos_token_id = self.eos_token_id if eos is None and self.add_eos_token: raise ValueError("add_eos_token = True but eos_token = None") single = f"{(bos+':0 ') if self.add_bos_token else ''}$A:0{(' '+eos+':0') if self.add_eos_token else ''}" pair = f"{single}{(' '+bos+':1') if self.add_bos_token else ''} $B:1{(' '+eos+':1') if self.add_eos_token else ''}" special_tokens = [] if self.add_bos_token: special_tokens.append((bos, bos_token_id)) if self.add_eos_token: special_tokens.append((eos, eos_token_id)) self._tokenizer.post_processor = processors.TemplateProcessing( single=single, pair=pair, special_tokens=special_tokens ) @property def add_eos_token(self): return self._add_eos_token @property def add_bos_token(self): return self._add_bos_token @add_eos_token.setter def add_eos_token(self, value): self._add_eos_token = value self.update_post_processor() @add_bos_token.setter def add_bos_token(self, value): self._add_bos_token = value self.update_post_processor() def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> Tuple[str]: if not self.can_save_slow_tokenizer: raise ValueError( "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow " "tokenizer." ) if not os.path.isdir(save_directory): logger.error(f"Vocabulary path ({save_directory}) should be a directory") return out_vocab_file = os.path.join( save_directory, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] ) if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file): copyfile(self.vocab_file, out_vocab_file) return (out_vocab_file,) def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): bos_token_id = [self.bos_token_id] if self.add_bos_token else [] eos_token_id = [self.eos_token_id] if self.add_eos_token else [] output = bos_token_id + token_ids_0 + eos_token_id if token_ids_1 is not None: output = output + bos_token_id + token_ids_1 + eos_token_id return output