Source code for modelzoo.transformers.data_processing.tokenizers.HFTokenizer

# Copyright 2022 Cerebras Systems.
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# Licensed under the Apache License, Version 2.0 (the "License");
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from tokenizers import Tokenizer


[docs]class HFTokenizer: """Designed to integrate the HF's Tokenizer library Args: vocab_file (str): A vocabulary file to create the tokenizer from. special_tokens (list, str): A list or a string representing the special tokens that are to be added to the tokenizer. """
[docs] def __init__(self, vocab_file, special_tokens=None): self.tokenizer = Tokenizer.from_file(vocab_file) if special_tokens: self.add_special_tokens(special_tokens) self.set_eos_pad_tokens()
def set_eos_pad_tokens(self): self.eos_id = self.get_token_id("<|endoftext|>") self.pad_id = self.get_token_id("<|padding|>") def encode(self, text): return self.tokenizer.encode(text).ids def decode(self, token_ids, skip_special_tokens=False): return self.tokenizer.decode( token_ids, skip_special_tokens=skip_special_tokens ) def add_special_tokens(self, special_tokens): self.tokenizer.add_special_tokens(special_tokens) def add_token(self, token): self.tokenizer.add_tokens(token) def get_token_id(self, token): return self.tokenizer.token_to_id(token) def get_token(self, id): return self.tokenizer.id_to_token(id) @property def eos(self): return self.eos_id @property def pad(self): return self.pad_id