Source code for matx.text.wordpiece_tokenizer

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import sys
from typing import List, Tuple, AnyStr, Any

from ..native import make_native_object
from ._dso_loader import load_text_ops_lib

load_text_ops_lib()
matx = sys.modules['matx']


[docs]class WordPieceTokenizerImpl(object):
[docs] def __init__(self, vocab_path: str, lookup_id: bool = True, unk_token: Any = "[UNK]", subwords_prefix: str = "##", skip_empty: bool = True, max_bytes_per_token: int = 100, ) -> None: self.native_tokenizer: Any = make_native_object( "text_tokenizer_WordPieceTokenizer", vocab_path, lookup_id, unk_token, subwords_prefix, skip_empty, max_bytes_per_token, )
[docs] def tokenize(self, sentence: List[AnyStr]) -> List[AnyStr]: return self.native_tokenizer.tokenize(sentence)
[docs] def tokenize_with_meta(self, sentence: List[AnyStr]) -> Tuple[List[AnyStr], List[int]]: return self.native_tokenizer.tokenize_with_meta(sentence)
[docs]class WordPieceTokenizer:
[docs] def __init__(self, vocab_path: str, lookup_id: bool = True, unk_token: Any = "[UNK]", subwords_prefix: str = "##", skip_empty: bool = True, max_bytes_per_token: int = 100, ) -> None: self.tokenizer_impl: WordPieceTokenizerImpl = matx.script(WordPieceTokenizerImpl)( vocab_path, lookup_id, unk_token, subwords_prefix, skip_empty, max_bytes_per_token)
[docs] def tokenize(self, sentence: List[AnyStr]) -> List[AnyStr]: return self.tokenizer_impl.tokenize(sentence)
[docs] def tokenizer_with_meta(self, sentence: List[AnyStr]) -> Tuple[List[AnyStr], List[int]]: return self.tokenizer_impl.tokenize_with_meta(sentence)