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# Copyright (c) Meta Platforms, Inc. and affiliates.
# This software may be used and distributed according to the terms of the GNU General Public License version 3.
from sentencepiece import SentencePieceProcessor
import sentencepiece.sentencepiece_model_pb2 as model
from logging import getLogger
from typing import List
import os
logger = getLogger()
class Tokenizer:
def __init__(self, model_path: str, num_aud_tokens: int):
# reload tokenizer
assert os.path.isfile(model_path), model_path
m = model.ModelProto()
m.ParseFromString(open(model_path, "rb").read())
special_tokens = [f'[AUD{i}]' for i in range(num_aud_tokens)]
for token in special_tokens:
new_token = model.ModelProto().SentencePiece()
new_token.piece = token
new_token.score = 0
if new_token in m.pieces:
m.pieces.remove(new_token)
m.pieces.append(new_token)
with open(model_path, 'wb') as f:
f.write(m.SerializeToString())
self.sp_model = SentencePieceProcessor(model_file=model_path)
logger.info(f"Reloaded SentencePiece model from {model_path}")
# BOS / EOS token IDs
self.n_words: int = self.sp_model.vocab_size()
self.bos_id: int = self.sp_model.bos_id()
self.eos_id: int = self.sp_model.eos_id()
self.pad_id: int = self.sp_model.pad_id()
logger.info(
f"#words: {self.n_words} - BOS ID: {self.bos_id} - EOS ID: {self.eos_id}"
)
assert self.sp_model.vocab_size() == self.sp_model.get_piece_size()
def encode(self, s: str, bos: bool = False, eos: bool = False) -> List[int]:
assert type(s) is str
t = self.sp_model.encode_as_ids(s)
if bos:
t = [self.bos_id] + t
if eos:
t = t + [self.eos_id]
return t
def decode(self, t: List[int]) -> str:
return self.sp_model.decode(t)
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