import os
import re
import unicodedata
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


__lowerCamelCase :     Dict          =  logging.get_logger(__name__)
__lowerCamelCase :     List[Any]          =  {'''vocab_file''': '''spiece.model'''}

__lowerCamelCase :     Dict          =  {
    '''vocab_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/spiece.model''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/spiece.model''',
    },
}

__lowerCamelCase :     str          =  {
    '''google/fnet-base''': 5_12,
    '''google/fnet-large''': 5_12,
}

__lowerCamelCase :     Optional[int]          =  '''▁'''






class 		a__						( _lowerCAmelCase ):
					A     	=							VOCAB_FILES_NAMES
					A     	=							PRETRAINED_VOCAB_FILES_MAP
					A     	=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A     	=							["input_ids", "token_type_ids"]

					def __init__(   self				:	str,_A				:	Tuple,_A				:	List[Any]=False,_A				:	List[str]=True,_A				:	Dict=True,_A				:	Dict="<unk>",_A				:	Tuple="[SEP]",_A				:	Optional[Any]="<pad>",_A				:	List[Any]="[CLS]",_A				:	str="[MASK]",_A				:	Optional[Dict[str, Any]] = None,**_A				:	Any,):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		List[str]    				=   (
								    AddedToken(_lowerCamelCase,lstrip=_lowerCamelCase,rstrip=_lowerCamelCase,normalized=_lowerCamelCase   )
								    if isinstance(_lowerCamelCase,_lowerCamelCase   )
								    else mask_token
								)

								SCREAMING_SNAKE_CASE_  :		Dict    				=   {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    do_lower_case=_lowerCamelCase,remove_space=_lowerCamelCase,keep_accents=_lowerCamelCase,unk_token=_lowerCamelCase,sep_token=_lowerCamelCase,pad_token=_lowerCamelCase,cls_token=_lowerCamelCase,mask_token=_lowerCamelCase,sp_model_kwargs=self.sp_model_kwargs,**_lowerCamelCase,)

								SCREAMING_SNAKE_CASE_  :		Tuple    				=   do_lower_case
								SCREAMING_SNAKE_CASE_  :		Any    				=   remove_space
								SCREAMING_SNAKE_CASE_  :		Dict    				=   keep_accents
								SCREAMING_SNAKE_CASE_  :		int    				=   vocab_file

								SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   spm.SentencePieceProcessor(**self.sp_model_kwargs   )
								self.sp_model.Load(_lowerCamelCase   )

					@property
					def     __UpperCamelCase       (   self				:	Tuple   ):







								"""simple docstring"""






								return len(self.sp_model   )

					def     __UpperCamelCase       (   self				:	List[str]   ):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		List[Any]    				=   {self.convert_ids_to_tokens(_lowerCamelCase   ): i for i in range(self.vocab_size   )}
								vocab.update(self.added_tokens_encoder   )
								return vocab

					def __getstate__(   self				:	int   ):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   self.__dict__.copy()
								SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   None
								return state

					def __setstate__(   self				:	Dict,_A				:	str   ):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		List[str]    				=   d

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

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

					def     __UpperCamelCase       (   self				:	List[Any],_A				:	Tuple   ):







								"""simple docstring"""






								if self.remove_space:
											SCREAMING_SNAKE_CASE_  :		str    				=   " ".join(inputs.strip().split()   )
								else:
											SCREAMING_SNAKE_CASE_  :		List[Any]    				=   inputs
								SCREAMING_SNAKE_CASE_  :		int    				=   outputs.replace("``","\""   ).replace("\'\'","\""   )

								if not self.keep_accents:
											SCREAMING_SNAKE_CASE_  :		Dict    				=   unicodedata.normalize("NFKD",_lowerCamelCase   )
											SCREAMING_SNAKE_CASE_  :		int    				=   "".join([c for c in outputs if not unicodedata.combining(_lowerCamelCase   )]   )
								if self.do_lower_case:
											SCREAMING_SNAKE_CASE_  :		str    				=   outputs.lower()

								return outputs

					def     __UpperCamelCase       (   self				:	Union[str, Any],_A				:	str   ):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   self.preprocess_text(_lowerCamelCase   )
								SCREAMING_SNAKE_CASE_  :		List[str]    				=   self.sp_model.encode(_lowerCamelCase,out_type=_lowerCamelCase   )
								SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   []
								for piece in pieces:
											if len(_lowerCamelCase   ) > 1 and piece[-1] == str(","   ) and piece[-2].isdigit():
														SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   self.sp_model.EncodeAsPieces(piece[:-1].replace(_lowerCamelCase,""   )   )
														if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																	if len(cur_pieces[0]   ) == 1:
																				SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   cur_pieces[1:]
																	else:
																				SCREAMING_SNAKE_CASE_  :		Dict    				=   cur_pieces[0][1:]
														cur_pieces.append(piece[-1]   )
														new_pieces.extend(_lowerCamelCase   )
											else:
														new_pieces.append(_lowerCamelCase   )

								return new_pieces

					def     __UpperCamelCase       (   self				:	Tuple,_A				:	str   ):







								"""simple docstring"""






								return self.sp_model.PieceToId(_lowerCamelCase   )

					def     __UpperCamelCase       (   self				:	Tuple,_A				:	int   ):







								"""simple docstring"""






								return self.sp_model.IdToPiece(_lowerCamelCase   )

					def     __UpperCamelCase       (   self				:	Any,_A				:	Optional[int]   ):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		Tuple    				=   []
								SCREAMING_SNAKE_CASE_  :		Tuple    				=   ""
								SCREAMING_SNAKE_CASE_  :		List[Any]    				=   False
								for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
														if not prev_is_special:
																	out_string += " "
														out_string += self.sp_model.decode(_lowerCamelCase   ) + token
														SCREAMING_SNAKE_CASE_  :		int    				=   True
														SCREAMING_SNAKE_CASE_  :		Tuple    				=   []
											else:
														current_sub_tokens.append(_lowerCamelCase   )
														SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   False
								out_string += self.sp_model.decode(_lowerCamelCase   )
								return out_string.strip()

					def     __UpperCamelCase       (   self				:	Any,_A				:	List[int],_A				:	bool = False,_A				:	bool = None,_A				:	bool = True,**_A				:	Optional[Any],):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		Dict    				=   kwargs.pop("use_source_tokenizer",_lowerCamelCase   )

								SCREAMING_SNAKE_CASE_  :		List[str]    				=   self.convert_ids_to_tokens(_lowerCamelCase,skip_special_tokens=_lowerCamelCase   )

								# To avoid mixing byte-level and unicode for byte-level BPT
								# we need to build string separately for added tokens and byte-level tokens
								# cf. https://github.com/huggingface/transformers/issues/1133
								SCREAMING_SNAKE_CASE_  :		int    				=   []
								SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   []
								for token in filtered_tokens:
											if skip_special_tokens and token in self.all_special_ids:
														continue
											if token in self.added_tokens_encoder:
														if current_sub_text:
																	sub_texts.append(self.convert_tokens_to_string(_lowerCamelCase   )   )
																	SCREAMING_SNAKE_CASE_  :		List[Any]    				=   []
														sub_texts.append(_lowerCamelCase   )
											else:
														current_sub_text.append(_lowerCamelCase   )
								if current_sub_text:
											sub_texts.append(self.convert_tokens_to_string(_lowerCamelCase   )   )

								# Mimic the behavior of the Rust tokenizer:
								# No space after <unk>
								if spaces_between_special_tokens:
											SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   re.sub(R"(<unk>) ",R"\1"," ".join(_lowerCamelCase   )   )
								else:
											SCREAMING_SNAKE_CASE_  :		int    				=   "".join(_lowerCamelCase   )

								SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   (
								    clean_up_tokenization_spaces
								    if clean_up_tokenization_spaces is not None
								    else self.clean_up_tokenization_spaces
								)
								if clean_up_tokenization_spaces:
											SCREAMING_SNAKE_CASE_  :		int    				=   self.clean_up_tokenization(_lowerCamelCase   )
											return clean_text
								else:
											return text

					def     __UpperCamelCase       (   self				:	str,_A				:	List[int],_A				:	Optional[List[int]] = None   ):







								"""simple docstring"""






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

					def     __UpperCamelCase       (   self				:	Dict,_A				:	List[int],_A				:	Optional[List[int]] = None,_A				:	bool = False   ):







								"""simple docstring"""






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

								if token_ids_a is not None:
											return [1] + ([0] * len(_lowerCamelCase   )) + [1] + ([0] * len(_lowerCamelCase   )) + [1]
								return [1] + ([0] * len(_lowerCamelCase   )) + [1]

					def     __UpperCamelCase       (   self				:	List[str],_A				:	List[int],_A				:	Optional[List[int]] = None   ):







								"""simple docstring"""






								SCREAMING_SNAKE_CASE_  :		Dict    				=   [self.sep_token_id]
								SCREAMING_SNAKE_CASE_  :		Tuple    				=   [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   ) * [0] + len(token_ids_a + sep   ) * [1]






					def     __UpperCamelCase       (   self				:	List[str],_A				:	str,_A				:	Optional[str] = None   ):







								"""simple docstring"""






								if not os.path.isdir(_lowerCamelCase   ):
											logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
											return
								SCREAMING_SNAKE_CASE_  :		List[str]    				=   os.path.join(
								    _lowerCamelCase,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )

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

								return (out_vocab_file,)

__lowerCamelCase :     List[Any]          =  {hex(i)[2:]: i for i in range(16)}  # Use [:2] to strip off the leading '0x'




def 				_snake_case     (       lowerCAmelCase							:       str     ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   hex_string.strip().lower()
		if not hex_string:
				raise ValueError("Empty string was passed to the function"     )
		SCREAMING_SNAKE_CASE_  :		str    				=   hex_string[0] == "-"
		if is_negative:
				SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   hex_string[1:]
		if not all(char in hex_table for char in hex_string     ):
				raise ValueError("Non-hexadecimal value was passed to the function"     )
		SCREAMING_SNAKE_CASE_  :		List[Any]    				=   0
		for char in hex_string:
				SCREAMING_SNAKE_CASE_  :		Tuple    				=   1_6 * decimal_number + hex_table[char]
		return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
		from doctest import testmod

		testmod()
