


'''simple docstring'''






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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A	:	str     =     logging.get_logger(__name__)


__A	:	Optional[int]     =     '▁'

__A	:	List[str]     =     {'vocab_file': 'spiece.model'}

__A	:	Union[str, Any]     =     {
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    }
}

__A	:	Any     =     {
    'google/reformer-crime-and-punishment': 524_288,
}
class 						__UpperCamelCase	(						lowercase__							):
							lowercase			:		List[Any]   		=  VOCAB_FILES_NAMES
							lowercase			:		Tuple   		=  PRETRAINED_VOCAB_FILES_MAP
							lowercase			:		str   		=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase			:		str   		=  ['input_ids', 'attention_mask']





							def __init__(  self		:str  ,_UpperCamelCase		:Optional[Any]  ,_UpperCamelCase		:Union[str, Any]="</s>"  ,_UpperCamelCase		:List[Any]="<unk>"  ,_UpperCamelCase		:str=[]  ,_UpperCamelCase		:Optional[Dict[str, Any]] = None  ,**_UpperCamelCase		:Dict  ,):
									snake_case_		:							Tuple			       =						{} if sp_model_kwargs is None else sp_model_kwargs

									super().__init__(
									    eos_token=_UpperCamelCase  ,unk_token=_UpperCamelCase  ,additional_special_tokens=_UpperCamelCase  ,sp_model_kwargs=self.sp_model_kwargs  ,**_UpperCamelCase  ,)

									snake_case_		:							Union[str, Any]			       =						vocab_file
									snake_case_		:							Dict			       =						spm.SentencePieceProcessor(**self.sp_model_kwargs			)
									self.sp_model.Load(_UpperCamelCase			)





							@property
							def 		a__   (  self		:List[Any]			):
									return self.sp_model.get_piece_size()





							def 		a__   (  self		:Any			):
									snake_case_		:							Any			       =						{self.convert_ids_to_tokens(_UpperCamelCase			): i for i in range(self.vocab_size			)}
									vocab.update(self.added_tokens_encoder			)
									return vocab





							def __getstate__(  self		:str			):
									snake_case_		:							List[str]			       =						self.__dict__.copy()
									snake_case_		:							int			       =						None
									return state





							def __setstate__(  self		:str  ,_UpperCamelCase		:Optional[Any]			):
									snake_case_		:							List[Any]			       =						d

									# for backward compatibility
									if not hasattr(self  ,"""sp_model_kwargs"""			):
											snake_case_		:							Any			       =						{}

									snake_case_		:							List[Any]			       =						spm.SentencePieceProcessor(**self.sp_model_kwargs			)
									self.sp_model.Load(self.vocab_file			)





							def 		a__   (  self		:List[Any]  ,_UpperCamelCase		:str			):
									return self.sp_model.encode(_UpperCamelCase  ,out_type=_UpperCamelCase			)





							def 		a__   (  self		:Tuple  ,_UpperCamelCase		:Optional[Any]			):
									return self.sp_model.piece_to_id(_UpperCamelCase			)





							def 		a__   (  self		:int  ,_UpperCamelCase		:List[str]			):
									if index < self.sp_model.get_piece_size():
											snake_case_		:							Any			       =						self.sp_model.IdToPiece(_UpperCamelCase			)
									return token





							def 		a__   (  self		:Any  ,_UpperCamelCase		:List[Any]			):
									snake_case_		:							Any			       =						[]
									snake_case_		:							int			       =						""""""
									for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
													out_string += self.sp_model.decode(_UpperCamelCase			) + token
													snake_case_		:							Any			       =						[]
											else:
													current_sub_tokens.append(_UpperCamelCase			)
									out_string += self.sp_model.decode(_UpperCamelCase			)
									return out_string.strip()





							def 		a__   (  self		:Tuple  ,_UpperCamelCase		:str  ,_UpperCamelCase		:Optional[str] = None			):
									if not os.path.isdir(_UpperCamelCase			):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
											return
									snake_case_		:							Tuple			       =						os.path.join(
									    _UpperCamelCase  ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""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:
													snake_case_		:							Tuple			       =						self.sp_model.serialized_model_proto()
													fi.write(_UpperCamelCase			)

									return (out_vocab_file,)



'''simple docstring'''






import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class 						__UpperCamelCase	(						lowercase__						,  unittest.TestCase							):
							lowercase			:		Dict   		=  TransfoXLTokenizer
							lowercase			:		Optional[Any]   		=  False
							lowercase			:		Dict   		=  False





							def 		a__   (  self		:Union[str, Any]			):
									super().setUp()

									snake_case_		:							Optional[int]			       =						[
									    """<unk>""",
									    """[CLS]""",
									    """[SEP]""",
									    """want""",
									    """unwanted""",
									    """wa""",
									    """un""",
									    """running""",
									    """,""",
									    """low""",
									    """l""",
									]
									snake_case_		:							Optional[int]			       =						os.path.join(self.tmpdirname  ,VOCAB_FILES_NAMES["""vocab_file"""]			)
									with open(self.vocab_file  ,"""w"""  ,encoding="""utf-8"""			) as vocab_writer:
											vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]			)			)





							def 		a__   (  self		:List[Any]  ,**_UpperCamelCase		:Optional[Any]			):
									snake_case_		:							Tuple			       =						True
									return TransfoXLTokenizer.from_pretrained(self.tmpdirname  ,**_UpperCamelCase			)





							def 		a__   (  self		:Tuple  ,_UpperCamelCase		:Union[str, Any]			):
									snake_case_		:							Any			       =						"""<unk> UNwanted , running"""
									snake_case_		:							Optional[int]			       =						"""<unk> unwanted, running"""
									return input_text, output_text





							def 		a__   (  self		:Dict			):
									snake_case_		:							Dict			       =						TransfoXLTokenizer(vocab_file=self.vocab_file  ,lower_case=_UpperCamelCase			)

									snake_case_		:							Dict			       =						tokenizer.tokenize("""<unk> UNwanted , running"""			)
									self.assertListEqual(_UpperCamelCase  ,["""<unk>""", """unwanted""", """,""", """running"""]			)

									self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase			)  ,[0, 4, 8, 7]			)





							def 		a__   (  self		:Optional[Any]			):
									snake_case_		:							Dict			       =						TransfoXLTokenizer(lower_case=_UpperCamelCase			)

									self.assertListEqual(
									    tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """			)  ,["""hello""", """!""", """how""", """are""", """you""", """?"""]			)





							def 		a__   (  self		:Any			):
									snake_case_		:							List[Any]			       =						TransfoXLTokenizer(lower_case=_UpperCamelCase			)

									self.assertListEqual(
									    tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """			)  ,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]			)





							def 		a__   (  self		:List[str]			):
									snake_case_		:							str			       =						TransfoXLTokenizer(lower_case=_UpperCamelCase			)
									snake_case_		:							List[str]			       =						"""Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"""
									snake_case_		:							Optional[int]			       =						[
									    """Hello""",
									    """(""",
									    """bracket""",
									    """)""",
									    """and""",
									    """side""",
									    """@-@""",
									    """scrolled""",
									    """[""",
									    """and""",
									    """]""",
									    """Henry""",
									    """'s""",
									    """$""",
									    """5""",
									    """@,@""",
									    """000""",
									    """with""",
									    """3""",
									    """@.@""",
									    """34""",
									    """m""",
									    """.""",
									    """What""",
									    """'s""",
									    """up""",
									    """!""",
									    """?""",
									]

									self.assertListEqual(tokenizer.tokenize(_UpperCamelCase			)  ,_UpperCamelCase			)

									self.assertEqual(tokenizer.convert_tokens_to_string(_UpperCamelCase			)  ,_UpperCamelCase			)





							def 		a__   (  self		:Dict			):
									snake_case_		:							Union[str, Any]			       =						self.get_tokenizer()
									snake_case_		:							Dict			       =						len(_UpperCamelCase			)

									tokenizer.add_tokens(["""new1""", """new2"""]			)
									tokenizer.move_added_token("""new1"""  ,1			)

									# Check that moved token is not copied (duplicate)
									self.assertEqual(len(_UpperCamelCase			)  ,original_len + 2			)
									# Check that token is moved to specified id
									self.assertEqual(tokenizer.encode("""new1"""			)  ,[1]			)
									self.assertEqual(tokenizer.decode([1]			)  ,"""new1"""			)