Spaces:
Runtime error
Runtime error
import os | |
import torch | |
class SPieceTokenizer: | |
add_eos = True | |
def from_pretrained(path): | |
return SPieceTokenizer(path) | |
def __init__(self, tokenizer_path): | |
import sentencepiece | |
if torch.is_tensor(tokenizer_path): | |
tokenizer_path = tokenizer_path.numpy().tobytes() | |
if isinstance(tokenizer_path, bytes): | |
self.tokenizer = sentencepiece.SentencePieceProcessor(model_proto=tokenizer_path, add_eos=self.add_eos) | |
else: | |
self.tokenizer = sentencepiece.SentencePieceProcessor(model_file=tokenizer_path, add_eos=self.add_eos) | |
def get_vocab(self): | |
out = {} | |
for i in range(self.tokenizer.get_piece_size()): | |
out[self.tokenizer.id_to_piece(i)] = i | |
return out | |
def __call__(self, string): | |
out = self.tokenizer.encode(string) | |
return {"input_ids": out} | |
def serialize_model(self): | |
return torch.ByteTensor(list(self.tokenizer.serialized_model_proto())) | |