






import os
import re
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      	=  {'''vocab_file''': '''spiece.model'''}

_a      	=  {
    '''vocab_file''': {
        '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model''',
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'''
        ),
    }
}

_a      	=  {
    '''google/bigbird-roberta-base''': 4096,
    '''google/bigbird-roberta-large''': 4096,
    '''google/bigbird-base-trivia-itc''': 4096,
}





class __lowerCamelCase (      __A):





	"""simple docstring"""






	UpperCamelCase__								=      VOCAB_FILES_NAMES
	UpperCamelCase__								=      PRETRAINED_VOCAB_FILES_MAP
	UpperCamelCase__								=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	UpperCamelCase__								=      ["input_ids", "attention_mask"]
	UpperCamelCase__								=      []

	def __init__(							self       ,    UpperCAmelCase       ,    UpperCAmelCase="<unk>"       ,    UpperCAmelCase="<s>"       ,    UpperCAmelCase="</s>"       ,    UpperCAmelCase="<pad>"       ,    UpperCAmelCase="[SEP]"       ,    UpperCAmelCase="[MASK]"       ,    UpperCAmelCase="[CLS]"       ,    UpperCAmelCase = None       ,    **UpperCAmelCase       ,    ):
							"""simple docstring"""







							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else bos_token
							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else eos_token
							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else unk_token
							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else pad_token
							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else cls_token
							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else sep_token

							# Mask token behave like a normal word, i.e. include the space before it
							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else mask_token

							_UpperCAmelCase									=			{} if sp_model_kwargs is None else sp_model_kwargs

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

							_UpperCAmelCase									=			vocab_file

							_UpperCAmelCase									=			spm.SentencePieceProcessor(**self.sp_model_kwargs    )
							self.sp_model.Load(_UpperCamelCase    )

	@property
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							return self.sp_model.get_piece_size()

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			{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    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self.__dict__.copy()
							_UpperCAmelCase									=			None
							return state

	def __setstate__(							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			d

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

							_UpperCAmelCase									=			spm.SentencePieceProcessor(**self.sp_model_kwargs    )
							self.sp_model.Load(self.vocab_file    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							return self.sp_model.encode(_UpperCamelCase       ,    out_type=_UpperCamelCase    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							return self.sp_model.piece_to_id(_UpperCamelCase    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self.sp_model.IdToPiece(_UpperCamelCase    )
							return token

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			[]
							_UpperCAmelCase									=			''
							_UpperCAmelCase									=			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(_UpperCamelCase    ) + token
																			_UpperCAmelCase									=			True
																			_UpperCAmelCase									=			[]
													else:
																			current_sub_tokens.append(_UpperCamelCase    )
																			_UpperCAmelCase									=			False
							out_string += self.sp_model.decode(_UpperCamelCase    )
							return out_string.strip()

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = False       ,    UpperCAmelCase = None       ,    UpperCAmelCase = True       ,    **UpperCAmelCase       ,    ):
							"""simple docstring"""







							_UpperCAmelCase									=			kwargs.pop('use_source_tokenizer'       ,    _UpperCamelCase    )

							_UpperCAmelCase									=			self.convert_ids_to_tokens(_UpperCamelCase       ,    skip_special_tokens=_UpperCamelCase    )

							# 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
							_UpperCAmelCase									=			[]
							_UpperCAmelCase									=			[]
							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(_UpperCamelCase    )    )
																									_UpperCAmelCase									=			[]
																			sub_texts.append(_UpperCamelCase    )
													else:
																			current_sub_text.append(_UpperCamelCase    )
							if current_sub_text:
													sub_texts.append(self.convert_tokens_to_string(_UpperCamelCase    )    )

							# Mimic the behavior of the Rust tokenizer:
							# No space before [MASK] and [SEP]
							if spaces_between_special_tokens:
													_UpperCAmelCase									=			re.sub(R' (\[(MASK|SEP)\])'       ,    R'\1'       ,    ' '.join(_UpperCamelCase    )    )
							else:
													_UpperCAmelCase									=			''.join(_UpperCamelCase    )

							_UpperCAmelCase									=			(
							    clean_up_tokenization_spaces
							    if clean_up_tokenization_spaces is not None
							    else self.clean_up_tokenization_spaces
							)
							if clean_up_tokenization_spaces:
													_UpperCAmelCase									=			self.clean_up_tokenization(_UpperCamelCase    )
													return clean_text
							else:
													return text

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = None    ):
							"""simple docstring"""







							if not os.path.isdir(_UpperCamelCase    ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
													return
							_UpperCAmelCase									=			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:
																			_UpperCAmelCase									=			self.sp_model.serialized_model_proto()
																			fi.write(_UpperCamelCase    )

							return (out_vocab_file,)

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = None    ):
							"""simple docstring"""







							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							_UpperCAmelCase									=			[self.cls_token_id]
							_UpperCAmelCase									=			[self.sep_token_id]
							return cls + token_ids_a + sep + token_ids_a + sep

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = None       ,    UpperCAmelCase = False    ):
							"""simple docstring"""







							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] + ([0] * len(_UpperCamelCase    )) + [1]

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = None    ):
							"""simple docstring"""







							_UpperCAmelCase									=			[self.sep_token_id]
							_UpperCAmelCase									=			[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   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	[]
						if len(SCREAMING_SNAKE_CASE__       ) == 1:
												return [nums.copy()]
						for _ in range(len(SCREAMING_SNAKE_CASE__       )       ):
												snake_case_   =	nums.pop(0       )
												snake_case_   =	permute(SCREAMING_SNAKE_CASE__       )
												for perm in permutations:
																		perm.append(SCREAMING_SNAKE_CASE__       )
												result.extend(SCREAMING_SNAKE_CASE__       )
												nums.append(SCREAMING_SNAKE_CASE__       )
						return result


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):

						def backtrack(SCREAMING_SNAKE_CASE__       ):
												if start == len(SCREAMING_SNAKE_CASE__       ) - 1:
																		output.append(nums[:]       )
												else:
																		for i in range(SCREAMING_SNAKE_CASE__  ,		len(SCREAMING_SNAKE_CASE__       )       ):
																								snake_case_,    snake_case_   =	nums[i], nums[start]
																								backtrack(start + 1       )
																								snake_case_,    snake_case_   =	nums[i], nums[start]  # backtrack

						snake_case_   =	[]
						backtrack(0       )
						return output


if __name__ == "__main__":
					import doctest

					# use res to print the data in permute2 function
					lowerCAmelCase_       	=	permutea([1, 2, 3])
					print(res)
					doctest.testmod()