


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

import sentencepiece as spm

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


lowerCAmelCase       		=    logging.get_logger(__name__)

lowerCAmelCase       		=    """▁"""

lowerCAmelCase       		=    {"""vocab_file""": """sentencepiece.bpe.model"""}

lowerCAmelCase       		=    {
    """vocab_file""": {
        """facebook/nllb-200-distilled-600M""": (
            """https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model"""
        ),
    }
}

lowerCAmelCase       		=    {
    """facebook/nllb-200-distilled-600M""": 1_024,
}

# fmt: off
lowerCAmelCase       		=    ["""ace_Arab""", """ace_Latn""", """acm_Arab""", """acq_Arab""", """aeb_Arab""", """afr_Latn""", """ajp_Arab""", """aka_Latn""", """amh_Ethi""", """apc_Arab""", """arb_Arab""", """ars_Arab""", """ary_Arab""", """arz_Arab""", """asm_Beng""", """ast_Latn""", """awa_Deva""", """ayr_Latn""", """azb_Arab""", """azj_Latn""", """bak_Cyrl""", """bam_Latn""", """ban_Latn""", """bel_Cyrl""", """bem_Latn""", """ben_Beng""", """bho_Deva""", """bjn_Arab""", """bjn_Latn""", """bod_Tibt""", """bos_Latn""", """bug_Latn""", """bul_Cyrl""", """cat_Latn""", """ceb_Latn""", """ces_Latn""", """cjk_Latn""", """ckb_Arab""", """crh_Latn""", """cym_Latn""", """dan_Latn""", """deu_Latn""", """dik_Latn""", """dyu_Latn""", """dzo_Tibt""", """ell_Grek""", """eng_Latn""", """epo_Latn""", """est_Latn""", """eus_Latn""", """ewe_Latn""", """fao_Latn""", """pes_Arab""", """fij_Latn""", """fin_Latn""", """fon_Latn""", """fra_Latn""", """fur_Latn""", """fuv_Latn""", """gla_Latn""", """gle_Latn""", """glg_Latn""", """grn_Latn""", """guj_Gujr""", """hat_Latn""", """hau_Latn""", """heb_Hebr""", """hin_Deva""", """hne_Deva""", """hrv_Latn""", """hun_Latn""", """hye_Armn""", """ibo_Latn""", """ilo_Latn""", """ind_Latn""", """isl_Latn""", """ita_Latn""", """jav_Latn""", """jpn_Jpan""", """kab_Latn""", """kac_Latn""", """kam_Latn""", """kan_Knda""", """kas_Arab""", """kas_Deva""", """kat_Geor""", """knc_Arab""", """knc_Latn""", """kaz_Cyrl""", """kbp_Latn""", """kea_Latn""", """khm_Khmr""", """kik_Latn""", """kin_Latn""", """kir_Cyrl""", """kmb_Latn""", """kon_Latn""", """kor_Hang""", """kmr_Latn""", """lao_Laoo""", """lvs_Latn""", """lij_Latn""", """lim_Latn""", """lin_Latn""", """lit_Latn""", """lmo_Latn""", """ltg_Latn""", """ltz_Latn""", """lua_Latn""", """lug_Latn""", """luo_Latn""", """lus_Latn""", """mag_Deva""", """mai_Deva""", """mal_Mlym""", """mar_Deva""", """min_Latn""", """mkd_Cyrl""", """plt_Latn""", """mlt_Latn""", """mni_Beng""", """khk_Cyrl""", """mos_Latn""", """mri_Latn""", """zsm_Latn""", """mya_Mymr""", """nld_Latn""", """nno_Latn""", """nob_Latn""", """npi_Deva""", """nso_Latn""", """nus_Latn""", """nya_Latn""", """oci_Latn""", """gaz_Latn""", """ory_Orya""", """pag_Latn""", """pan_Guru""", """pap_Latn""", """pol_Latn""", """por_Latn""", """prs_Arab""", """pbt_Arab""", """quy_Latn""", """ron_Latn""", """run_Latn""", """rus_Cyrl""", """sag_Latn""", """san_Deva""", """sat_Beng""", """scn_Latn""", """shn_Mymr""", """sin_Sinh""", """slk_Latn""", """slv_Latn""", """smo_Latn""", """sna_Latn""", """snd_Arab""", """som_Latn""", """sot_Latn""", """spa_Latn""", """als_Latn""", """srd_Latn""", """srp_Cyrl""", """ssw_Latn""", """sun_Latn""", """swe_Latn""", """swh_Latn""", """szl_Latn""", """tam_Taml""", """tat_Cyrl""", """tel_Telu""", """tgk_Cyrl""", """tgl_Latn""", """tha_Thai""", """tir_Ethi""", """taq_Latn""", """taq_Tfng""", """tpi_Latn""", """tsn_Latn""", """tso_Latn""", """tuk_Latn""", """tum_Latn""", """tur_Latn""", """twi_Latn""", """tzm_Tfng""", """uig_Arab""", """ukr_Cyrl""", """umb_Latn""", """urd_Arab""", """uzn_Latn""", """vec_Latn""", """vie_Latn""", """war_Latn""", """wol_Latn""", """xho_Latn""", """ydd_Hebr""", """yor_Latn""", """yue_Hant""", """zho_Hans""", """zho_Hant""", """zul_Latn"""]




class 							lowerCamelCase   (  _UpperCamelCase ):
	_lowerCAmelCase     :		Union[str, Any]										=						VOCAB_FILES_NAMES
	_lowerCAmelCase     :		int										=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_lowerCAmelCase     :		Any										=						PRETRAINED_VOCAB_FILES_MAP
	_lowerCAmelCase     :		List[str]										=						['''input_ids''', '''attention_mask''']

	_lowerCAmelCase     :		List[int]										=						[]
	_lowerCAmelCase     :		List[int]										=						[]


	def __init__(    self				,     lowercase__				,     lowercase__="<s>"				,     lowercase__="</s>"				,     lowercase__="</s>"				,     lowercase__="<s>"				,     lowercase__="<unk>"				,     lowercase__="<pad>"				,     lowercase__="<mask>"				,     lowercase__=None				,     lowercase__=None				,     lowercase__=None				,     lowercase__ = None				,     lowercase__=None				,     lowercase__=False				,     **lowercase__				,     ):
							# Mask token behave like a normal word, i.e. include the space before it
							__UpperCAmelCase			:							int	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else mask_token

							__UpperCAmelCase			:							int	    =	{} if sp_model_kwargs is None else sp_model_kwargs
							__UpperCAmelCase			:							Union[str, Any]	    =	legacy_behaviour

							super().__init__(
							    bos_token=lowercase__				,     eos_token=lowercase__				,     unk_token=lowercase__				,     sep_token=lowercase__				,     cls_token=lowercase__				,     pad_token=lowercase__				,     mask_token=lowercase__				,     tokenizer_file=lowercase__				,     src_lang=lowercase__				,     tgt_lang=lowercase__				,     additional_special_tokens=lowercase__				,     sp_model_kwargs=self.sp_model_kwargs				,     legacy_behaviour=lowercase__				,     **lowercase__				,     )

							__UpperCAmelCase			:							Any	    =	spm.SentencePieceProcessor(**self.sp_model_kwargs)
							self.sp_model.Load(str(lowercase__))
							__UpperCAmelCase			:							Any	    =	vocab_file
							# Original fairseq vocab and spm vocab must be "aligned":
							# Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
							# -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
							# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
							# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

							# Mimic fairseq token-to-id alignment for the first 4 token
							__UpperCAmelCase			:							str	    =	{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

							# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
							__UpperCAmelCase			:							Tuple	    =	1

							__UpperCAmelCase			:							List[str]	    =	len(self.sp_model)
							__UpperCAmelCase			:							int	    =	{
							    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowercase__)
							}
							__UpperCAmelCase			:							List[Any]	    =	{v: k for k, v in self.lang_code_to_id.items()}
							__UpperCAmelCase			:							Dict	    =	len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

							self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
							__UpperCAmelCase			:							Dict	    =	{v: k for k, v in self.fairseq_tokens_to_ids.items()}
							__UpperCAmelCase			:							List[str]	    =	list(self.lang_code_to_id.keys())

							if additional_special_tokens is not None:
													# Only add those special tokens if they are not already there.
													self._additional_special_tokens.extend(
													    [t for t in additional_special_tokens if t not in self._additional_special_tokens])

							__UpperCAmelCase			:							Optional[int]	    =	src_lang if src_lang is not None else '''eng_Latn'''
							__UpperCAmelCase			:							Optional[int]	    =	self.lang_code_to_id[self._src_lang]
							__UpperCAmelCase			:							List[Any]	    =	tgt_lang
							self.set_src_lang_special_tokens(self._src_lang)


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


	def __setstate__(    self				,     lowercase__):
							__UpperCAmelCase			:							Optional[Any]	    =	d

							# for backward compatibility
							if not hasattr(self				,     '''sp_model_kwargs'''):
													__UpperCAmelCase			:							Tuple	    =	{}

							__UpperCAmelCase			:							Optional[int]	    =	spm.SentencePieceProcessor(**self.sp_model_kwargs)
							self.sp_model.LoadFromSerializedProto(self.sp_model_proto)


	@property
	def  A(    self):
							return len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset + 1  # Plus 1 for the mask token


	@property
	def  A(    self):
							return self._src_lang


	@src_lang.setter
	def  A(    self				,     lowercase__):
							__UpperCAmelCase			:							Optional[Any]	    =	new_src_lang
							self.set_src_lang_special_tokens(self._src_lang)


	def  A(    self				,     lowercase__				,     lowercase__ = None				,     lowercase__ = False):

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

							__UpperCAmelCase			:							str	    =	[1] * len(self.prefix_tokens)
							__UpperCAmelCase			:							List[Any]	    =	[1] * len(self.suffix_tokens)
							if token_ids_a is None:
													return prefix_ones + ([0] * len(lowercase__)) + suffix_ones
							return prefix_ones + ([0] * len(lowercase__)) + ([0] * len(lowercase__)) + suffix_ones


	def  A(    self				,     lowercase__				,     lowercase__ = None):
							if token_ids_a is None:
													return self.prefix_tokens + token_ids_a + self.suffix_tokens
							# We don't expect to process pairs, but leave the pair logic for API consistency
							return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens


	def  A(    self				,     lowercase__				,     lowercase__ = None):
							__UpperCAmelCase			:							Union[str, Any]	    =	[self.sep_token_id]
							__UpperCAmelCase			:							List[Any]	    =	[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]


	def  A(    self				,     lowercase__				,     lowercase__				,     lowercase__				,     lowercase__				,     **lowercase__):
							if src_lang is None or tgt_lang is None:
													raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model''')
							__UpperCAmelCase			:							Any	    =	src_lang
							__UpperCAmelCase			:							List[str]	    =	self(lowercase__				,     add_special_tokens=lowercase__				,     return_tensors=lowercase__				,     **lowercase__)
							__UpperCAmelCase			:							Optional[Any]	    =	self.convert_tokens_to_ids(lowercase__)
							__UpperCAmelCase			:							Union[str, Any]	    =	tgt_lang_id
							return inputs


	def  A(    self):
							__UpperCAmelCase			:							Dict	    =	{self.convert_ids_to_tokens(lowercase__): i for i in range(self.vocab_size)}
							vocab.update(self.added_tokens_encoder)
							return vocab


	def  A(    self				,     lowercase__):
							return self.sp_model.encode(lowercase__				,     out_type=lowercase__)


	def  A(    self				,     lowercase__):
							if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
							__UpperCAmelCase			:							Tuple	    =	self.sp_model.PieceToId(lowercase__)

							# Need to return unknown token if the SP model returned 0
							return spm_id + self.fairseq_offset if spm_id else self.unk_token_id


	def  A(    self				,     lowercase__):
							if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
							return self.sp_model.IdToPiece(index - self.fairseq_offset)


	def  A(    self				,     lowercase__):
							__UpperCAmelCase			:							Tuple	    =	''''''.join(lowercase__).replace(lowercase__				,     ''' ''').strip()
							return out_string


	def  A(    self				,     lowercase__				,     lowercase__ = None):
							if not os.path.isdir(lowercase__):
													logger.error(F"Vocabulary path ({save_directory}) should be a directory")
													return
							__UpperCAmelCase			:							int	    =	os.path.join(
							    lowercase__				,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

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

							return (out_vocab_file,)


	def  A(    self				,     lowercase__				,     lowercase__ = "eng_Latn"				,     lowercase__ = None				,     lowercase__ = "fra_Latn"				,     **lowercase__				,     ):
							__UpperCAmelCase			:							int	    =	src_lang
							__UpperCAmelCase			:							Tuple	    =	tgt_lang
							return super().prepare_seqaseq_batch(lowercase__				,     lowercase__				,     **lowercase__)


	def  A(    self):
							return self.set_src_lang_special_tokens(self.src_lang)


	def  A(    self):
							return self.set_tgt_lang_special_tokens(self.tgt_lang)


	def  A(    self				,     lowercase__):
							__UpperCAmelCase			:							Union[str, Any]	    =	self.lang_code_to_id[src_lang]
							if self.legacy_behaviour:
													__UpperCAmelCase			:							Optional[int]	    =	[]
													__UpperCAmelCase			:							Dict	    =	[self.eos_token_id, self.cur_lang_code]
							else:
													__UpperCAmelCase			:							Dict	    =	[self.cur_lang_code]
													__UpperCAmelCase			:							Optional[int]	    =	[self.eos_token_id]


	def  A(    self				,     lowercase__):
							__UpperCAmelCase			:							str	    =	self.lang_code_to_id[lang]
							if self.legacy_behaviour:
													__UpperCAmelCase			:							List[str]	    =	[]
													__UpperCAmelCase			:							str	    =	[self.eos_token_id, self.cur_lang_code]
							else:
													__UpperCAmelCase			:							Optional[int]	    =	[self.cur_lang_code]
													__UpperCAmelCase			:							Tuple	    =	[self.eos_token_id]





import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


lowerCAmelCase       		=    logging.get_logger(__name__)


lowerCAmelCase       		=    {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all LED models at https://huggingface.co/models?filter=LED
lowerCAmelCase       		=    {
    """vocab_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json""",
    },
}

lowerCAmelCase       		=    {
    """allenai/led-base-16384""": 16_384,
}




@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def     __SCREAMING_SNAKE_CASE							(       )		->     Dict:




						'''simple docstring'''







						__UpperCAmelCase			:							Optional[int]	    =	(
						    list(range(ord('''!'''      )      ,       ord('''~'''      ) + 1      )      ) + list(range(ord('''¡'''      )      ,       ord('''¬'''      ) + 1      )      ) + list(range(ord('''®'''      )      ,       ord('''ÿ'''      ) + 1      )      )
						)
						__UpperCAmelCase			:							Tuple	    =	bs[:]
						__UpperCAmelCase			:							Dict	    =	0
						for b in range(2**8      ):
												if b not in bs:
																		bs.append(lowercase_      )
																		cs.append(2**8 + n      )
																		n += 1
						__UpperCAmelCase			:							Union[str, Any]	    =	[chr(lowercase_      ) for n in cs]
						return dict(zip(lowercase_      ,       lowercase_      )      )




def     __SCREAMING_SNAKE_CASE							(       lowercase_      )		->     Optional[Any]:




						'''simple docstring'''







						__UpperCAmelCase			:							Any	    =	set()
						__UpperCAmelCase			:							Tuple	    =	word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)      )
												__UpperCAmelCase			:							Tuple	    =	char
						return pairs





class 							lowerCamelCase   (  _UpperCamelCase ):
	_lowerCAmelCase     :		List[Any]										=						VOCAB_FILES_NAMES
	_lowerCAmelCase     :		int										=						PRETRAINED_VOCAB_FILES_MAP
	_lowerCAmelCase     :		Union[str, Any]										=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_lowerCAmelCase     :		int										=						['''input_ids''', '''attention_mask''']


	def __init__(    self				,     lowercase__				,     lowercase__				,     lowercase__="replace"				,     lowercase__="<s>"				,     lowercase__="</s>"				,     lowercase__="</s>"				,     lowercase__="<s>"				,     lowercase__="<unk>"				,     lowercase__="<pad>"				,     lowercase__="<mask>"				,     lowercase__=False				,     **lowercase__				,     ):
							__UpperCAmelCase			:							List[Any]	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else bos_token
							__UpperCAmelCase			:							int	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else eos_token
							__UpperCAmelCase			:							Optional[Any]	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else sep_token
							__UpperCAmelCase			:							Any	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else cls_token
							__UpperCAmelCase			:							Any	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else unk_token
							__UpperCAmelCase			:							List[str]	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else pad_token

							# Mask token behave like a normal word, i.e. include the space before it
							__UpperCAmelCase			:							Optional[Any]	    =	AddedToken(lowercase__				,     lstrip=lowercase__				,     rstrip=lowercase__) if isinstance(lowercase__				,     lowercase__) else mask_token

							super().__init__(
							    errors=lowercase__				,     bos_token=lowercase__				,     eos_token=lowercase__				,     unk_token=lowercase__				,     sep_token=lowercase__				,     cls_token=lowercase__				,     pad_token=lowercase__				,     mask_token=lowercase__				,     add_prefix_space=lowercase__				,     **lowercase__				,     )

							with open(lowercase__				,     encoding='''utf-8''') as vocab_handle:
													__UpperCAmelCase			:							Optional[int]	    =	json.load(lowercase__)
							__UpperCAmelCase			:							List[str]	    =	{v: k for k, v in self.encoder.items()}
							__UpperCAmelCase			:							Optional[Any]	    =	errors  # how to handle errors in decoding
							__UpperCAmelCase			:							str	    =	bytes_to_unicode()
							__UpperCAmelCase			:							List[str]	    =	{v: k for k, v in self.byte_encoder.items()}
							with open(lowercase__				,     encoding='''utf-8''') as merges_handle:
													__UpperCAmelCase			:							Optional[int]	    =	merges_handle.read().split('''\n''')[1:-1]
							__UpperCAmelCase			:							int	    =	[tuple(merge.split()) for merge in bpe_merges]
							__UpperCAmelCase			:							str	    =	dict(zip(lowercase__				,     range(len(lowercase__))))
							__UpperCAmelCase			:							Optional[int]	    =	{}
							__UpperCAmelCase			:							Optional[int]	    =	add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							__UpperCAmelCase			:							List[Any]	    =	re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+''')


	@property
	# Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
	def  A(    self):
							return len(self.encoder)


	def  A(    self):
							return dict(self.encoder				,     **self.added_tokens_encoder)


	def  A(    self				,     lowercase__):
							if token in self.cache:
													return self.cache[token]
							__UpperCAmelCase			:							int	    =	tuple(lowercase__)
							__UpperCAmelCase			:							int	    =	get_pairs(lowercase__)

							if not pairs:
													return token

							while True:
													__UpperCAmelCase			:							Union[str, Any]	    =	min(lowercase__				,     key=lambda lowercase__: self.bpe_ranks.get(lowercase__				,     float('''inf''')))
													if bigram not in self.bpe_ranks:
																			break
													__UpperCAmelCase    ,      __UpperCAmelCase			:							Tuple	    =	bigram
													__UpperCAmelCase			:							List[str]	    =	[]
													__UpperCAmelCase			:							List[str]	    =	0
													while i < len(lowercase__):
																			try:
																									__UpperCAmelCase			:							List[Any]	    =	word.index(lowercase__				,     lowercase__)
																			except ValueError:
																									new_word.extend(word[i:])
																									break
																			else:
																									new_word.extend(word[i:j])
																									__UpperCAmelCase			:							str	    =	j

																			if word[i] == first and i < len(lowercase__) - 1 and word[i + 1] == second:
																									new_word.append(first + second)
																									i += 2
																			else:
																									new_word.append(word[i])
																									i += 1
													__UpperCAmelCase			:							Union[str, Any]	    =	tuple(lowercase__)
													__UpperCAmelCase			:							Dict	    =	new_word
													if len(lowercase__) == 1:
																			break
													else:
																			__UpperCAmelCase			:							Optional[int]	    =	get_pairs(lowercase__)
							__UpperCAmelCase			:							List[Any]	    =	''' '''.join(lowercase__)
							__UpperCAmelCase			:							Tuple	    =	word
							return word


	def  A(    self				,     lowercase__):
							__UpperCAmelCase			:							str	    =	[]
							for token in re.findall(self.pat				,     lowercase__):
													__UpperCAmelCase			:							Dict	    =	''''''.join(
													    self.byte_encoder[b] for b in token.encode('''utf-8'''))  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
													bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowercase__).split(''' '''))
							return bpe_tokens


	def  A(    self				,     lowercase__):
							return self.encoder.get(lowercase__				,     self.encoder.get(self.unk_token))


	def  A(    self				,     lowercase__):
							return self.decoder.get(lowercase__)


	def  A(    self				,     lowercase__):
							__UpperCAmelCase			:							str	    =	''''''.join(lowercase__)
							__UpperCAmelCase			:							Optional[int]	    =	bytearray([self.byte_decoder[c] for c in text]).decode('''utf-8'''				,     errors=self.errors)
							return text


	def  A(    self				,     lowercase__				,     lowercase__ = None):
							if not os.path.isdir(lowercase__):
													logger.error(F"Vocabulary path ({save_directory}) should be a directory")
													return
							__UpperCAmelCase			:							List[Any]	    =	os.path.join(
							    lowercase__				,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])
							__UpperCAmelCase			:							Optional[Any]	    =	os.path.join(
							    lowercase__				,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file'''])

							with open(lowercase__				,     '''w'''				,     encoding='''utf-8''') as f:
													f.write(json.dumps(self.encoder				,     indent=2				,     sort_keys=lowercase__				,     ensure_ascii=lowercase__) + '''\n''')

							__UpperCAmelCase			:							Tuple	    =	0
							with open(lowercase__				,     '''w'''				,     encoding='''utf-8''') as writer:
													writer.write('''#version: 0.2\n''')
													for bpe_tokens, token_index in sorted(self.bpe_ranks.items()				,     key=lambda lowercase__: kv[1]):
																			if index != token_index:
																									logger.warning(
																									    F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
																									    ''' Please check that the tokenizer is not corrupted!''')
																									__UpperCAmelCase			:							Optional[int]	    =	token_index
																			writer.write(''' '''.join(lowercase__) + '''\n''')
																			index += 1

							return vocab_file, merge_file


	def  A(    self				,     lowercase__				,     lowercase__ = None):
							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							__UpperCAmelCase			:							Optional[Any]	    =	[self.cls_token_id]
							__UpperCAmelCase			:							Union[str, Any]	    =	[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep


	def  A(    self				,     lowercase__				,     lowercase__ = None				,     lowercase__ = False):
							if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=lowercase__				,     token_ids_a=lowercase__				,     already_has_special_tokens=lowercase__)

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


	def  A(    self				,     lowercase__				,     lowercase__ = None):
							__UpperCAmelCase			:							List[Any]	    =	[self.sep_token_id]
							__UpperCAmelCase			:							List[Any]	    =	[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]


	def  A(    self				,     lowercase__				,     lowercase__=False				,     **lowercase__):
							__UpperCAmelCase			:							List[Any]	    =	kwargs.pop('''add_prefix_space'''				,     self.add_prefix_space)
							if (is_split_into_words or add_prefix_space) and (len(lowercase__) > 0 and not text[0].isspace()):
													__UpperCAmelCase			:							List[Any]	    =	''' ''' + text
							return (text, kwargs)


	def  A(    self				,     lowercase__				,     lowercase__ = None				,     lowercase__ = PaddingStrategy.DO_NOT_PAD				,     lowercase__ = None				,     lowercase__ = None				,     ):
							__UpperCAmelCase			:							Optional[Any]	    =	super()._pad(
							    encoded_inputs=lowercase__				,     max_length=lowercase__				,     padding_strategy=lowercase__				,     pad_to_multiple_of=lowercase__				,     return_attention_mask=lowercase__				,     )

							# Load from model defaults
							if return_attention_mask is None:
													__UpperCAmelCase			:							Optional[Any]	    =	'''attention_mask''' in self.model_input_names

							if return_attention_mask and "global_attention_mask" in encoded_inputs:
													__UpperCAmelCase			:							Dict	    =	encoded_inputs[self.model_input_names[0]]
													# `global_attention_mask` need to have the same length as other (sequential) inputs.
													__UpperCAmelCase			:							int	    =	len(encoded_inputs['''global_attention_mask''']) != len(lowercase__)

													if needs_to_be_padded:
																			__UpperCAmelCase			:							Dict	    =	len(lowercase__) - len(encoded_inputs['''global_attention_mask'''])

																			if self.padding_side == "right":
																									# Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
																									__UpperCAmelCase			:							Optional[Any]	    =	(
																									    encoded_inputs['''global_attention_mask'''] + [-1] * difference
																									)
																			elif self.padding_side == "left":
																									__UpperCAmelCase			:							int	    =	[-1] * difference + encoded_inputs[
																									    '''global_attention_mask'''
																									]
																			else:
																									raise ValueError('''Invalid padding strategy:''' + str(self.padding_side))

							return encoded_inputs

