


'''simple docstring'''



import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__A	=logging.get_logger(__name__)

__A	='▁'

__A	={'vocab_file': 'sentencepiece.bpe.model', 'monolingual_vocab_file': 'dict.txt'}

__A	={
    'vocab_file': {
        'vinai/bartpho-syllable': 'https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model',
    },
    'monolingual_vocab_file': {
        'vinai/bartpho-syllable': 'https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt',
    },
}

__A	={'vinai/bartpho-syllable': 10_24}


class 		_snake_case					(     snake_case__	):
					lowerCAmelCase      :Dict   =					VOCAB_FILES_NAMES
					lowerCAmelCase      :str   =					PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase      :Optional[int]   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase      :Tuple   =					["""input_ids""", """attention_mask"""]




					def __init__(      self							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase="<s>"							,							_lowerCamelCase="</s>"							,							_lowerCamelCase="</s>"							,							_lowerCamelCase="<s>"							,							_lowerCamelCase="<unk>"							,							_lowerCamelCase="<pad>"							,							_lowerCamelCase="<mask>"							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								UpperCAmelCase__  :					Union[str, Any]        =     AddedToken(UpperCAmelCase_							,							lstrip=UpperCAmelCase_							,							rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_							,							UpperCAmelCase_) else mask_token

								UpperCAmelCase__  :					Any        =     {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=UpperCAmelCase_							,							eos_token=UpperCAmelCase_							,							unk_token=UpperCAmelCase_							,							sep_token=UpperCAmelCase_							,							cls_token=UpperCAmelCase_							,							pad_token=UpperCAmelCase_							,							mask_token=UpperCAmelCase_							,							sp_model_kwargs=self.sp_model_kwargs							,							**UpperCAmelCase_							,							)

								UpperCAmelCase__  :					List[Any]        =     vocab_file
								UpperCAmelCase__  :					Tuple        =     monolingual_vocab_file
								UpperCAmelCase__  :					List[Any]        =     spm.SentencePieceProcessor(**self.sp_model_kwargs)
								self.sp_model.Load(str(UpperCAmelCase_))

								# Load the reduced vocab

								# Keep order of special tokens for backward compatibility
								UpperCAmelCase__  :					List[str]        =     {}
								UpperCAmelCase__  :					Union[str, Any]        =     0
								for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
											if str(UpperCAmelCase_) not in self.fairseq_tokens_to_ids:
														UpperCAmelCase__  :					int        =     cnt
														cnt += 1
								with open(UpperCAmelCase_							,							"""r"""							,							encoding="""utf-8""") as f:
											for line in f.readlines():
														UpperCAmelCase__  :					Tuple        =     line.strip().split()[0]
														UpperCAmelCase__  :					Tuple        =     len(self.fairseq_tokens_to_ids)
								if str(UpperCAmelCase_) not in self.fairseq_tokens_to_ids:
											UpperCAmelCase__  :					Any        =     len(self.fairseq_tokens_to_ids)

								UpperCAmelCase__  :					Optional[int]        =     {v: k for k, v in self.fairseq_tokens_to_ids.items()}




					def __getstate__(      self):
								UpperCAmelCase__  :					Optional[int]        =     self.__dict__.copy()
								UpperCAmelCase__  :					List[str]        =     None
								UpperCAmelCase__  :					Union[str, Any]        =     self.sp_model.serialized_model_proto()
								return state




					def __setstate__(      self							,							_lowerCamelCase):
								UpperCAmelCase__  :					Any        =     d

								# for backward compatibility
								if not hasattr(self							,							"""sp_model_kwargs"""):
											UpperCAmelCase__  :					Optional[Any]        =     {}

								UpperCAmelCase__  :					List[str]        =     spm.SentencePieceProcessor(**self.sp_model_kwargs)
								self.sp_model.LoadFromSerializedProto(self.sp_model_proto)




					def 				snake_case__						(      self							,							_lowerCamelCase							,							_lowerCamelCase = None):



								if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								UpperCAmelCase__  :					List[Any]        =     [self.cls_token_id]
								UpperCAmelCase__  :					Optional[Any]        =     [self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep




					def 				snake_case__						(      self							,							_lowerCamelCase							,							_lowerCamelCase = None							,							_lowerCamelCase = False):



								if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=UpperCAmelCase_							,							token_ids_a=UpperCAmelCase_							,							already_has_special_tokens=UpperCAmelCase_)

								if token_ids_a is None:
											return [1] + ([0] * len(UpperCAmelCase_)) + [1]
								return [1] + ([0] * len(UpperCAmelCase_)) + [1, 1] + ([0] * len(UpperCAmelCase_)) + [1]




					def 				snake_case__						(      self							,							_lowerCamelCase							,							_lowerCamelCase = None):
								UpperCAmelCase__  :					Union[str, Any]        =     [self.sep_token_id]
								UpperCAmelCase__  :					str        =     [self.cls_token_id]

								if token_ids_a is None:
											return len(cls + token_ids_a + sep) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]




					@property
					def 				snake_case__						(      self):
								return len(self.fairseq_ids_to_tokens)




					def 				snake_case__						(      self):
								UpperCAmelCase__  :					int        =     {self.convert_ids_to_tokens(UpperCAmelCase_): i for i in range(self.vocab_size)}
								vocab.update(self.added_tokens_encoder)
								return vocab




					def 				snake_case__						(      self							,							_lowerCamelCase):
								return self.sp_model.encode(UpperCAmelCase_							,							out_type=UpperCAmelCase_)




					def 				snake_case__						(      self							,							_lowerCamelCase):



								if token in self.fairseq_tokens_to_ids:
											return self.fairseq_tokens_to_ids[token]
								else:
											return self.unk_token_id




					def 				snake_case__						(      self							,							_lowerCamelCase):
								return self.fairseq_ids_to_tokens[index]




					def 				snake_case__						(      self							,							_lowerCamelCase):
								UpperCAmelCase__  :					Optional[Any]        =     """""".join(UpperCAmelCase_).replace(UpperCAmelCase_							,							""" """).strip()
								return out_string




					def 				snake_case__						(      self							,							_lowerCamelCase							,							_lowerCamelCase = None):



								if not os.path.isdir(UpperCAmelCase_):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory''')
											return
								UpperCAmelCase__  :					int        =     os.path.join(
								    UpperCAmelCase_							,							(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])
								UpperCAmelCase__  :					Any        =     os.path.join(
								    UpperCAmelCase_							,							(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""monolingual_vocab_file"""]							,							)

								if os.path.abspath(self.vocab_file) != os.path.abspath(UpperCAmelCase_) and os.path.isfile(self.vocab_file):
											copyfile(self.vocab_file							,							UpperCAmelCase_)
								elif not os.path.isfile(self.vocab_file):
											with open(UpperCAmelCase_							,							"""wb""") as fi:
														UpperCAmelCase__  :					Optional[int]        =     self.sp_model.serialized_model_proto()
														fi.write(UpperCAmelCase_)

								if os.path.abspath(self.monolingual_vocab_file) != os.path.abspath(
								    UpperCAmelCase_) and os.path.isfile(self.monolingual_vocab_file):
											copyfile(self.monolingual_vocab_file							,							UpperCAmelCase_)
								elif not os.path.isfile(self.monolingual_vocab_file):
											with open(UpperCAmelCase_							,							"""w"""							,							encoding="""utf-8""") as fp:
														for token in self.fairseq_tokens_to_ids:
																	if token not in self.all_special_tokens:
																				fp.write(f'''{str(UpperCAmelCase_)} \n''')

								return out_vocab_file, out_monolingual_vocab_file



'''simple docstring'''



import warnings
from functools import wraps
from typing import Callable







def     _UpperCamelCase      (		UpperCamelCase__					):

			@wraps(UpperCamelCase__					)
			def _inner_fn(*UpperCamelCase__ ,      **UpperCamelCase__					):
						warnings.warn(
						    (f'''\'{fn.__name__}\' is experimental and might be subject to breaking changes in the future.''') ,      UpperCamelCase__ ,      )
						return fn(*UpperCamelCase__ ,      **UpperCamelCase__					)

			return _inner_fn