


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


lowerCamelCase						=		logging.get_logger(__name__)

lowerCamelCase						=		{'''vocab_file''': '''spiece.model'''}

lowerCamelCase						=		{
    '''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'''
        ),
    }
}

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





class  _a							(    _UpperCamelCase):
	_a  :  Tuple				   =							VOCAB_FILES_NAMES
	_a  :  Dict				   =							PRETRAINED_VOCAB_FILES_MAP
	_a  :  List[Any]				   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_a  :  int				   =							['input_ids', 'attention_mask']
	_a  :  List[int]				   =							[]




	def __init__( self						:		int		, _SCREAMING_SNAKE_CASE						:		str		, _SCREAMING_SNAKE_CASE						:		List[str]="<unk>"		, _SCREAMING_SNAKE_CASE						:		str="<s>"		, _SCREAMING_SNAKE_CASE						:		Any="</s>"		, _SCREAMING_SNAKE_CASE						:		Any="<pad>"		, _SCREAMING_SNAKE_CASE						:		Tuple="[SEP]"		, _SCREAMING_SNAKE_CASE						:		int="[MASK]"		, _SCREAMING_SNAKE_CASE						:		List[str]="[CLS]"		, _SCREAMING_SNAKE_CASE						:		Optional[Dict[str, Any]] = None		, **_SCREAMING_SNAKE_CASE						:		List[str]		, )->	Optional[int]:
			lowerCAmelCase__       :      List[Any]   					= AddedToken(_UpperCAmelCase		, lstrip=_UpperCAmelCase		, rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase		, _UpperCAmelCase		) else bos_token
			lowerCAmelCase__       :      Dict   					= AddedToken(_UpperCAmelCase		, lstrip=_UpperCAmelCase		, rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase		, _UpperCAmelCase		) else eos_token
			lowerCAmelCase__       :      List[Any]   					= AddedToken(_UpperCAmelCase		, lstrip=_UpperCAmelCase		, rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase		, _UpperCAmelCase		) else unk_token
			lowerCAmelCase__       :      List[str]   					= AddedToken(_UpperCAmelCase		, lstrip=_UpperCAmelCase		, rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase		, _UpperCAmelCase		) else pad_token
			lowerCAmelCase__       :      Dict   					= AddedToken(_UpperCAmelCase		, lstrip=_UpperCAmelCase		, rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase		, _UpperCAmelCase		) else cls_token
			lowerCAmelCase__       :      Optional[int]   					= 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
			lowerCAmelCase__       :      Optional[Any]   					= AddedToken(_UpperCAmelCase		, lstrip=_UpperCAmelCase		, rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase		, _UpperCAmelCase		) else mask_token

			lowerCAmelCase__       :      Optional[int]   					= {} 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		, )

			lowerCAmelCase__       :      int   					= vocab_file

			lowerCAmelCase__       :      Optional[int]   					= spm.SentencePieceProcessor(**self.sp_model_kwargs		)
			self.sp_model.Load(_UpperCAmelCase		)




	@property
	def 							UpperCAmelCase__( self						:		Union[str, Any]		)->	Union[str, Any]:
			return self.sp_model.get_piece_size()




	def 							UpperCAmelCase__( self						:		str		)->	List[str]:
			lowerCAmelCase__       :      Dict   					= {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						:		List[Any]		)->	int:
			lowerCAmelCase__       :      List[str]   					= self.__dict__.copy()
			lowerCAmelCase__       :      Union[str, Any]   					= None
			return state




	def __setstate__( self						:		List[Any]		, _SCREAMING_SNAKE_CASE						:		Dict		)->	Any:
			lowerCAmelCase__       :      List[str]   					= d

			# for backward compatibility
			if not hasattr(self		, '''sp_model_kwargs'''		):
					lowerCAmelCase__       :      Optional[Any]   					= {}

			lowerCAmelCase__       :      Optional[int]   					= spm.SentencePieceProcessor(**self.sp_model_kwargs		)
			self.sp_model.Load(self.vocab_file		)




	def 							UpperCAmelCase__( self						:		Optional[Any]		, _SCREAMING_SNAKE_CASE						:		str		)->	Tuple:
			return self.sp_model.encode(_UpperCAmelCase		, out_type=_UpperCAmelCase		)




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		Any		)->	Union[str, Any]:
			return self.sp_model.piece_to_id(_UpperCAmelCase		)




	def 							UpperCAmelCase__( self						:		List[Any]		, _SCREAMING_SNAKE_CASE						:		Tuple		)->	int:
			lowerCAmelCase__       :      Tuple   					= self.sp_model.IdToPiece(_UpperCAmelCase		)
			return token




	def 							UpperCAmelCase__( self						:		Tuple		, _SCREAMING_SNAKE_CASE						:		Optional[int]		)->	List[Any]:
			lowerCAmelCase__       :      Union[str, Any]   					= []
			lowerCAmelCase__       :      int   					= ''
			lowerCAmelCase__       :      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(_UpperCAmelCase		) + token
							lowerCAmelCase__       :      Dict   					= True
							lowerCAmelCase__       :      Tuple   					= []
					else:
							current_sub_tokens.append(_UpperCAmelCase		)
							lowerCAmelCase__       :      List[str]   					= False
			out_string += self.sp_model.decode(_UpperCAmelCase		)
			return out_string.strip()




	def 							UpperCAmelCase__( self						:		List[Any]		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		bool = False		, _SCREAMING_SNAKE_CASE						:		bool = None		, _SCREAMING_SNAKE_CASE						:		bool = True		, **_SCREAMING_SNAKE_CASE						:		List[str]		, )->	int:
			lowerCAmelCase__       :      Optional[Any]   					= kwargs.pop('''use_source_tokenizer'''		, _UpperCAmelCase		)

			lowerCAmelCase__       :      List[Any]   					= 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
			lowerCAmelCase__       :      str   					= []
			lowerCAmelCase__       :      int   					= []
			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		)		)
									lowerCAmelCase__       :      Dict   					= []
							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:
					lowerCAmelCase__       :      List[str]   					= re.sub(r''' (\[(MASK|SEP)\])'''		, r'''\1'''		, ''' '''.join(_UpperCAmelCase		)		)
			else:
					lowerCAmelCase__       :      str   					= ''.join(_UpperCAmelCase		)

			lowerCAmelCase__       :      str   					= (
			    clean_up_tokenization_spaces
			    if clean_up_tokenization_spaces is not None
			    else self.clean_up_tokenization_spaces
			)
			if clean_up_tokenization_spaces:
					lowerCAmelCase__       :      List[str]   					= self.clean_up_tokenization(_UpperCAmelCase		)
					return clean_text
			else:
					return text




	def 							UpperCAmelCase__( self						:		Any		, _SCREAMING_SNAKE_CASE						:		str		, _SCREAMING_SNAKE_CASE						:		Optional[str] = None		)->	List[Any]:
			if not os.path.isdir(_UpperCAmelCase		):
					logger.error(F'Vocabulary path ({save_directory}) should be a directory'		)
					return
			lowerCAmelCase__       :      str   					= 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:
							lowerCAmelCase__       :      Optional[int]   					= self.sp_model.serialized_model_proto()
							fi.write(_UpperCAmelCase		)

			return (out_vocab_file,)




	def 							UpperCAmelCase__( self						:		List[str]		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		Optional[List[int]] = None		)->	Optional[Any]:
			if token_ids_a is None:
					return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
			lowerCAmelCase__       :      Any   					= [self.cls_token_id]
			lowerCAmelCase__       :      str   					= [self.sep_token_id]
			return cls + token_ids_a + sep + token_ids_a + sep




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		Optional[List[int]] = None		, _SCREAMING_SNAKE_CASE						:		bool = False		)->	int:
			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						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		Optional[List[int]] = None		)->	Any:
			lowerCAmelCase__       :      Any   					= [self.sep_token_id]
			lowerCAmelCase__       :      Optional[int]   					= [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]



# using dfs for finding eulerian path traversal






def 					lowerCamelCase_   (	_a     ,       _a     ,       _a     ,       _a=None	):




		"""simple docstring"""






		lowerCAmelCase__       :      Optional[Any]   					= (path or []) + [u]
		for v in graph[u]:
				if visited_edge[u][v] is False:
						lowerCAmelCase__					,     lowerCAmelCase__       :      List[Any]   					= True, True
						lowerCAmelCase__       :      Any   					= dfs(_a     ,       _a     ,       _a     ,       _a	)
		return path






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		lowerCAmelCase__       :      Union[str, Any]   					= 0
		lowerCAmelCase__       :      str   					= -1
		for i in range(_a	):
				if i not in graph.keys():
						continue
				if len(graph[i]	) % 2 == 1:
						odd_degree_nodes += 1
						lowerCAmelCase__       :      Tuple   					= i
		if odd_degree_nodes == 0:
				return 1, odd_node
		if odd_degree_nodes == 2:
				return 2, odd_node
		return 3, odd_node






def 					lowerCamelCase_   (	_a     ,       _a	):




		"""simple docstring"""






		lowerCAmelCase__       :      Optional[Any]   					= [[False for _ in range(max_node + 1	)] for _ in range(max_node + 1	)]
		lowerCAmelCase__					,     lowerCAmelCase__       :      Optional[int]   					= check_circuit_or_path(_a     ,       _a	)
		if check == 3:
				print('''graph is not Eulerian'''	)
				print('''no path'''	)
				return
		lowerCAmelCase__       :      Optional[int]   					= 1
		if check == 2:
				lowerCAmelCase__       :      Any   					= odd_node
				print('''graph has a Euler path'''	)
		if check == 1:
				print('''graph has a Euler cycle'''	)
		lowerCAmelCase__       :      Optional[int]   					= dfs(_a     ,       _a     ,       _a	)
		print(_a	)






def 					lowerCamelCase_   (	):




		"""simple docstring"""






		lowerCAmelCase__       :      List[str]   					= {1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
		lowerCAmelCase__       :      Tuple   					= {1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
		lowerCAmelCase__       :      str   					= {1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
		lowerCAmelCase__       :      List[str]   					= {1: [2, 3], 2: [1, 3], 3: [1, 2]}
		lowerCAmelCase__       :      List[Any]   					= {
		    1: [],
		    2: []
		    # all degree is zero
		}
		lowerCAmelCase__       :      Optional[Any]   					= 10
		check_euler(_a     ,       _a	)
		check_euler(_a     ,       _a	)
		check_euler(_a     ,       _a	)
		check_euler(_a     ,       _a	)
		check_euler(_a     ,       _a	)


if __name__ == "__main__":
		main()




