


import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class        _lowercase      (			A__						,			unittest.TestCase       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			Optional[Any]						=		LongformerTokenizer
				SCREAMING_SNAKE_CASE__				:			Optional[Any]						=		True
				SCREAMING_SNAKE_CASE__				:			List[Any]						=		LongformerTokenizerFast
				SCREAMING_SNAKE_CASE__				:			List[str]						=		True


				def 		__magic_name__(       self			:List[str]	)		->			Union[str, Any]:
										super().setUp()

										# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
										__SCREAMING_SNAKE_CASE						:     Any					=		[
										    '''l''',
										    '''o''',
										    '''w''',
										    '''e''',
										    '''r''',
										    '''s''',
										    '''t''',
										    '''i''',
										    '''d''',
										    '''n''',
										    '''\u0120''',
										    '''\u0120l''',
										    '''\u0120n''',
										    '''\u0120lo''',
										    '''\u0120low''',
										    '''er''',
										    '''\u0120lowest''',
										    '''\u0120newer''',
										    '''\u0120wider''',
										    '''<unk>''',
										]
										__SCREAMING_SNAKE_CASE						:     List[str]					=		dict(zip(lowerCAmelCase__			,			range(len(lowerCAmelCase__	)	)	)	)
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		{'''unk_token''': '''<unk>'''}

										__SCREAMING_SNAKE_CASE						:     Tuple					=		os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''vocab_file''']	)
										__SCREAMING_SNAKE_CASE						:     Tuple					=		os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''merges_file''']	)
										with open(self.vocab_file			,			'''w'''			,			encoding='''utf-8'''	) as fp:
																fp.write(json.dumps(lowerCAmelCase__	) + '''\n'''	)
										with open(self.merges_file			,			'''w'''			,			encoding='''utf-8'''	) as fp:
																fp.write('''\n'''.join(lowerCAmelCase__	)	)


				def 		__magic_name__(       self			:Dict			,			**lowerCAmelCase__			:Any	)		->			Optional[int]:
										kwargs.update(self.special_tokens_map	)
										return self.tokenizer_class.from_pretrained(self.tmpdirname			,			**lowerCAmelCase__	)


				def 		__magic_name__(       self			:int			,			**lowerCAmelCase__			:List[Any]	)		->			str:
										kwargs.update(self.special_tokens_map	)
										return self.rust_tokenizer_class.from_pretrained(self.tmpdirname			,			**lowerCAmelCase__	)


				def 		__magic_name__(       self			:Tuple			,			lowerCAmelCase__			:int	)		->			int:
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		'''lower newer'''
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		'''lower newer'''
										return input_text, output_text


				def 		__magic_name__(       self			:List[Any]	)		->			List[str]:
										__SCREAMING_SNAKE_CASE						:     List[str]					=		self.tokenizer_class(self.vocab_file			,			self.merges_file			,			**self.special_tokens_map	)
										__SCREAMING_SNAKE_CASE						:     str					=		'''lower newer'''
										__SCREAMING_SNAKE_CASE						:     int					=		['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		tokenizer.tokenize(lowerCAmelCase__	)  # , add_prefix_space=True)
										self.assertListEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Dict					=		tokens + [tokenizer.unk_token]
										__SCREAMING_SNAKE_CASE						:     int					=		[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__	)			,			lowerCAmelCase__	)


				def 		__magic_name__(       self			:Optional[int]	)		->			List[Any]:
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		self.get_tokenizer()

										self.assertListEqual(tokenizer.encode('''Hello world!'''			,			add_special_tokens=lowerCAmelCase__	)			,			[0, 31_414, 232, 328, 2]	)
										self.assertListEqual(
										    tokenizer.encode('''Hello world! cécé herlolip 418'''			,			add_special_tokens=lowerCAmelCase__	)			,			[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]			,			)


				@slow
				def 		__magic_name__(       self			:Union[str, Any]	)		->			List[Any]:
										__SCREAMING_SNAKE_CASE						:     Any					=		self.tokenizer_class.from_pretrained('''allenai/longformer-base-4096'''	)

										__SCREAMING_SNAKE_CASE						:     int					=		tokenizer.encode('''sequence builders'''			,			add_special_tokens=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		tokenizer.encode('''multi-sequence build'''			,			add_special_tokens=lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     int					=		tokenizer.encode(
										    '''sequence builders'''			,			add_special_tokens=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer.encode(
										    '''sequence builders'''			,			'''multi-sequence build'''			,			add_special_tokens=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     int					=		tokenizer.build_inputs_with_special_tokens(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     str					=		tokenizer.build_inputs_with_special_tokens(lowerCAmelCase__			,			lowerCAmelCase__	)

										assert encoded_sentence == encoded_text_from_decode
										assert encoded_pair == encoded_pair_from_decode


				def 		__magic_name__(       self			:Tuple	)		->			Tuple:
										__SCREAMING_SNAKE_CASE						:     List[str]					=		self.get_tokenizer()

										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		'''Encode this sequence.'''
										__SCREAMING_SNAKE_CASE						:     List[str]					=		tokenizer.byte_encoder[''' '''.encode('''utf-8'''	)[0]]

										# Testing encoder arguments
										__SCREAMING_SNAKE_CASE						:     int					=		tokenizer.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Tuple					=		tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
										self.assertNotEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Tuple					=		tokenizer.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     int					=		tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
										self.assertEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}	)
										__SCREAMING_SNAKE_CASE						:     List[str]					=		tokenizer.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     str					=		tokenizer.convert_ids_to_tokens(encoded[1]	)[0]
										self.assertNotEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										# Testing spaces after special tokens
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		'''<mask>'''
										tokenizer.add_special_tokens(
										    {'''mask_token''': AddedToken(lowerCAmelCase__			,			lstrip=lowerCAmelCase__			,			rstrip=lowerCAmelCase__	)}	)  # mask token has a left space
										__SCREAMING_SNAKE_CASE						:     str					=		tokenizer.convert_tokens_to_ids(lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Dict					=		'''Encode <mask> sequence'''
										__SCREAMING_SNAKE_CASE						:     Any					=		'''Encode <mask>sequence'''

										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		tokenizer.encode(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Tuple					=		encoded.index(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
										self.assertEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer.encode(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Dict					=		encoded.index(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Dict					=		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
										self.assertNotEqual(lowerCAmelCase__			,			lowerCAmelCase__	)


				def 		__magic_name__(       self			:Optional[Any]	)		->			List[Any]:
										pass


				def 		__magic_name__(       self			:int	)		->			Any:
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
																						__SCREAMING_SNAKE_CASE						:     Tuple					=		self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__			,			**lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		self.tokenizer_class.from_pretrained(lowerCAmelCase__			,			**lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		'''A, <mask> AllenNLP sentence.'''
																						__SCREAMING_SNAKE_CASE						:     str					=		tokenizer_r.encode_plus(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__			,			return_token_type_ids=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Tuple					=		tokenizer_p.encode_plus(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__			,			return_token_type_ids=lowerCAmelCase__	)

																						# token_type_ids should put 0 everywhere
																						self.assertEqual(sum(tokens_r['''token_type_ids''']	)			,			sum(tokens_p['''token_type_ids''']	)	)

																						# attention_mask should put 1 everywhere, so sum over length should be 1
																						self.assertEqual(
																						    sum(tokens_r['''attention_mask''']	) / len(tokens_r['''attention_mask''']	)			,			sum(tokens_p['''attention_mask''']	) / len(tokens_p['''attention_mask''']	)			,			)

																						__SCREAMING_SNAKE_CASE						:     str					=		tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']	)
																						__SCREAMING_SNAKE_CASE						:     Optional[int]					=		tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']	)

																						# Rust correctly handles the space before the mask while python doesnt
																						self.assertSequenceEqual(tokens_p['''input_ids''']			,			[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]	)
																						self.assertSequenceEqual(tokens_r['''input_ids''']			,			[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]	)

																						self.assertSequenceEqual(
																						    lowerCAmelCase__			,			['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']	)
																						self.assertSequenceEqual(
																						    lowerCAmelCase__			,			['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']	)


				def 		__magic_name__(       self			:Optional[int]	)		->			Any:
										for trim_offsets, add_prefix_space in itertools.product([True, False]			,			repeat=2	):
																__SCREAMING_SNAKE_CASE						:     Any					=		self.rust_tokenizer_class.from_pretrained(
																    self.tmpdirname			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)

																__SCREAMING_SNAKE_CASE						:     Dict					=		json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()	)
																__SCREAMING_SNAKE_CASE						:     List[Any]					=		json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()	)

																self.assertEqual(pre_tokenizer_state['''add_prefix_space''']			,			lowerCAmelCase__	)

																self.assertEqual(post_processor_state['''add_prefix_space''']			,			lowerCAmelCase__	)
																self.assertEqual(post_processor_state['''trim_offsets''']			,			lowerCAmelCase__	)



				def 		__magic_name__(       self			:Any	)		->			List[Any]:
										# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
										# `trim_offsets`
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
																						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
																						__SCREAMING_SNAKE_CASE						:     Optional[int]					=		f'''{text_of_1_token} {text_of_1_token}'''

																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     str					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(0, len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(len(lowerCAmelCase__	) + 1, len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)

																						__SCREAMING_SNAKE_CASE						:     str					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(0, len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(len(lowerCAmelCase__	) + 1, len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)

																						__SCREAMING_SNAKE_CASE						:     Dict					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Dict					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(0, len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(len(lowerCAmelCase__	), len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)

																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(0, len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(len(lowerCAmelCase__	), len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)

																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		f''' {text}'''

																						# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																						#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																						# )
																						# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																						# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																						# self.assertEqual(
																						#     encoding.offset_mapping[1],
																						#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																						# )

																						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(1, 1 + len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(1 + len(lowerCAmelCase__	) + 1, 1 + len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)

																						__SCREAMING_SNAKE_CASE						:     Tuple					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(0, 1 + len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(1 + len(lowerCAmelCase__	), 1 + len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)

																						__SCREAMING_SNAKE_CASE						:     Dict					=		self.rust_tokenizer_class.from_pretrained(
																						    lowerCAmelCase__			,			use_fast=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			trim_offsets=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Any					=		tokenizer_r(lowerCAmelCase__			,			return_offsets_mapping=lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
																						self.assertEqual(encoding.offset_mapping[0]			,			(0, 1 + len(lowerCAmelCase__	))	)
																						self.assertEqual(
																						    encoding.offset_mapping[1]			,			(1 + len(lowerCAmelCase__	), 1 + len(lowerCAmelCase__	) + 1 + len(lowerCAmelCase__	))			,			)


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


lowercase  :					int													=       logging.get_logger(__name__)


lowercase  :					Union[str, Any]													=       '▁'

lowercase  :					Tuple													=       {'vocab_file': 'spiece.model'}

lowercase  :					Dict													=       {
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    }
}

lowercase  :					Any													=       {
    'google/reformer-crime-and-punishment': 524288,
}




class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	_A								=     VOCAB_FILES_NAMES
	_A								=     PRETRAINED_VOCAB_FILES_MAP
	_A								=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A								=     ['input_ids', 'attention_mask']







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

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

								__UpperCamelCase	:   Optional[Any]			   =					vocab_file
								__UpperCamelCase	:   Dict			   =					spm.SentencePieceProcessor(**self.sp_model_kwargs						)
								self.sp_model.Load(a						)







	@property
	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> Any:
								return self.sp_model.get_piece_size()







	def    _lowerCamelCase				(					self		:Optional[int]						)		-> Dict[str, int]:
								__UpperCamelCase	:   str			   =					{self.convert_ids_to_tokens(a						): i for i in range(self.vocab_size						)}
								vocab.update(self.added_tokens_encoder						)
								return vocab







	def __getstate__(					self		:str						)		-> List[str]:
								__UpperCamelCase	:   Union[str, Any]			   =					self.__dict__.copy()
								__UpperCamelCase	:   Optional[Any]			   =					None
								return state







	def __setstate__(					self		:int     ,   a		:List[str]						)		-> int:
								__UpperCamelCase	:   Union[str, Any]			   =					d

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

								__UpperCamelCase	:   Any			   =					spm.SentencePieceProcessor(**self.sp_model_kwargs						)
								self.sp_model.Load(self.vocab_file						)







	def    _lowerCamelCase				(					self		:List[Any]     ,   a		:str						)		-> List[str]:
								return self.sp_model.encode(a     ,   out_type=a						)







	def    _lowerCamelCase				(					self		:Optional[int]     ,   a		:Optional[Any]						)		-> str:
								return self.sp_model.piece_to_id(a						)







	def    _lowerCamelCase				(					self		:Dict     ,   a		:Union[str, Any]						)		-> Optional[int]:
								if index < self.sp_model.get_piece_size():
															__UpperCamelCase	:   Optional[int]			   =					self.sp_model.IdToPiece(a						)
								return token







	def    _lowerCamelCase				(					self		:Dict     ,   a		:List[Any]						)		-> Dict:
								__UpperCamelCase	:   Optional[int]			   =					[]
								__UpperCamelCase	:   str			   =					""
								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(a						) + token
																						__UpperCamelCase	:   List[Any]			   =					[]
															else:
																						current_sub_tokens.append(a						)
								out_string += self.sp_model.decode(a						)
								return out_string.strip()







	def    _lowerCamelCase				(					self		:Optional[Any]     ,   a		:str     ,   a		:Optional[str] = None						)		-> Tuple[str]:
								if not os.path.isdir(a						):
															logger.error(f'Vocabulary path ({save_directory}) should be a directory'						)
															return
								__UpperCamelCase	:   List[Any]			   =					os.path.join(
								    a     ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

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

								return (out_vocab_file,)