

'''simple docstring'''






from __future__ import annotations

from collections import deque
from queue import Queue
from timeit import timeit

snake_case_       =       {
    'A': ['B', 'C'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F'],
    'D': ['B'],
    'E': ['B', 'F'],
    'F': ['C', 'E'],
}


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	dict  ,  SCREAMING_SNAKE_CASE_     :	str    )							->   list[str]:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_      :			Dict     =       {start}
      SCREAMING_SNAKE_CASE_      :			str     =       [start]
      SCREAMING_SNAKE_CASE_      :			Queue     =       Queue()
      queue.put(SCREAMING_SNAKE_CASE_    )
      while not queue.empty():
            SCREAMING_SNAKE_CASE_      :			Dict     =       queue.get()
            for w in graph[v]:
                  if w not in explored:
                        explored.add(SCREAMING_SNAKE_CASE_    )
                        result.append(SCREAMING_SNAKE_CASE_    )
                        queue.put(SCREAMING_SNAKE_CASE_    )
      return result


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	dict  ,  SCREAMING_SNAKE_CASE_     :	str    )							->   list[str]:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_      :			List[Any]     =       {start}
      SCREAMING_SNAKE_CASE_      :			Any     =       [start]
      SCREAMING_SNAKE_CASE_      :			Tuple     =       deque([start]    )
      while queue:
            SCREAMING_SNAKE_CASE_      :			str     =       queue.popleft()
            for child in graph[v]:
                  if child not in visited:
                        visited.add(SCREAMING_SNAKE_CASE_    )
                        result.append(SCREAMING_SNAKE_CASE_    )
                        queue.append(SCREAMING_SNAKE_CASE_    )
      return result


def 					__lowerCamelCase			(      SCREAMING_SNAKE_CASE_     :	str    )							->   None:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_      :			Dict     =       F"from __main__ import G, {name}"
      SCREAMING_SNAKE_CASE_      :			List[str]     =       1_0_0_0_0
      SCREAMING_SNAKE_CASE_      :			Any     =       timeit(F"{name}(G, 'A')"  ,  setup=SCREAMING_SNAKE_CASE_  ,  number=SCREAMING_SNAKE_CASE_    )
      print(F"{name:<35} finished {number} runs in {res:.5f} seconds"    )


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      benchmark_function('breadth_first_search')
      benchmark_function('breadth_first_search_with_deque')
      # breadth_first_search                finished 10000 runs in 0.20999 seconds
      # breadth_first_search_with_deque     finished 10000 runs in 0.01421 seconds









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_						     =  logging.get_logger(__name__)
lowerCamelCase_						     =  {"""vocab_file""": """spiece.model"""}

lowerCamelCase_						     =  {
    """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_						     =  {
    """google/fnet-base""": 5_1_2,
    """google/fnet-large""": 5_1_2,
}

lowerCamelCase_						     =  """▁"""




class 							a_ (						a_		):


							'''simple docstring'''






							__a:	Optional[int]     =    VOCAB_FILES_NAMES
							__a:	Union[str, Any]     =    PRETRAINED_VOCAB_FILES_MAP
							__a:	List[Any]     =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__a:	Any     =    ['''input_ids''', '''token_type_ids''']

							def __init__(		self			,			lowercase_			,			lowercase_=False			,			lowercase_=True			,			lowercase_=True			,			lowercase_="<unk>"			,			lowercase_="[SEP]"			,			lowercase_="<pad>"			,			lowercase_="[CLS]"			,			lowercase_="[MASK]"			,			lowercase_ = None			,			**lowercase_			,			)					->					None:
														'''simple docstring'''

														lowerCAmelCase_										=     (
														    AddedToken(lowercase_			,			lstrip=lowercase_			,			rstrip=lowercase_			,			normalized=lowercase_   )
														    if isinstance(lowercase_			,			lowercase_   )
														    else mask_token
														)

														lowerCAmelCase_										=     {} if sp_model_kwargs is None else sp_model_kwargs

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

														lowerCAmelCase_										=     do_lower_case
														lowerCAmelCase_										=     remove_space
														lowerCAmelCase_										=     keep_accents
														lowerCAmelCase_										=     vocab_file

														lowerCAmelCase_										=     spm.SentencePieceProcessor(**self.sp_model_kwargs   )
														self.sp_model.Load(lowercase_   )

							@property
							def      _lowercase       (		self   )					->					Optional[Any]:
														'''simple docstring'''

														return len(self.sp_model   )

							def      _lowercase       (		self   )					->					Dict:
														'''simple docstring'''

														lowerCAmelCase_										=     {self.convert_ids_to_tokens(lowercase_   ): i for i in range(self.vocab_size   )}
														vocab.update(self.added_tokens_encoder   )
														return vocab

							def __getstate__(		self   )					->					Dict:
														'''simple docstring'''

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

							def __setstate__(		self			,			lowercase_   )					->					Optional[int]:
														'''simple docstring'''

														lowerCAmelCase_										=     d

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

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

							def      _lowercase       (		self			,			lowercase_   )					->					str:
														'''simple docstring'''

														if self.remove_space:
																					lowerCAmelCase_										=     ' '.join(inputs.strip().split()   )
														else:
																					lowerCAmelCase_										=     inputs
														lowerCAmelCase_										=     outputs.replace('``'			,			'"'   ).replace('\'\''			,			'"'   )

														if not self.keep_accents:
																					lowerCAmelCase_										=     unicodedata.normalize('NFKD'			,			lowercase_   )
																					lowerCAmelCase_										=     ''.join([c for c in outputs if not unicodedata.combining(lowercase_   )]   )
														if self.do_lower_case:
																					lowerCAmelCase_										=     outputs.lower()

														return outputs

							def      _lowercase       (		self			,			lowercase_   )					->					List[str]:
														'''simple docstring'''

														lowerCAmelCase_										=     self.preprocess_text(lowercase_   )
														lowerCAmelCase_										=     self.sp_model.encode(lowercase_			,			out_type=lowercase_   )
														lowerCAmelCase_										=     []
														for piece in pieces:
																					if len(lowercase_   ) > 1 and piece[-1] == str(','   ) and piece[-2].isdigit():
																												lowerCAmelCase_										=     self.sp_model.EncodeAsPieces(piece[:-1].replace(lowercase_			,			''   )   )
																												if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																																			if len(cur_pieces[0]   ) == 1:
																																										lowerCAmelCase_										=     cur_pieces[1:]
																																			else:
																																										lowerCAmelCase_										=     cur_pieces[0][1:]
																												cur_pieces.append(piece[-1]   )
																												new_pieces.extend(lowercase_   )
																					else:
																												new_pieces.append(lowercase_   )

														return new_pieces

							def      _lowercase       (		self			,			lowercase_   )					->					Tuple:
														'''simple docstring'''

														return self.sp_model.PieceToId(lowercase_   )

							def      _lowercase       (		self			,			lowercase_   )					->					Union[str, Any]:
														'''simple docstring'''

														return self.sp_model.IdToPiece(lowercase_   )

							def      _lowercase       (		self			,			lowercase_   )					->					Union[str, Any]:
														'''simple docstring'''

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

							def      _lowercase       (		self			,			lowercase_			,			lowercase_ = False			,			lowercase_ = None			,			lowercase_ = True			,			**lowercase_			,			)					->					str:
														'''simple docstring'''

														lowerCAmelCase_										=     kwargs.pop('use_source_tokenizer'			,			lowercase_   )

														lowerCAmelCase_										=     self.convert_ids_to_tokens(lowercase_			,			skip_special_tokens=lowercase_   )

														# 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_										=     []
														lowerCAmelCase_										=     []
														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(lowercase_   )   )
																																			lowerCAmelCase_										=     []
																												sub_texts.append(lowercase_   )
																					else:
																												current_sub_text.append(lowercase_   )
														if current_sub_text:
																					sub_texts.append(self.convert_tokens_to_string(lowercase_   )   )

														# Mimic the behavior of the Rust tokenizer:
														# No space after <unk>
														if spaces_between_special_tokens:
																					lowerCAmelCase_										=     re.sub(R'(<unk>) '			,			R'\1'			,			' '.join(lowercase_   )   )
														else:
																					lowerCAmelCase_										=     ''.join(lowercase_   )

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

							def      _lowercase       (		self			,			lowercase_			,			lowercase_ = None   )					->					List[int]:
														'''simple docstring'''

														lowerCAmelCase_										=     [self.sep_token_id]
														lowerCAmelCase_										=     [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      _lowercase       (		self			,			lowercase_			,			lowercase_ = None			,			lowercase_ = False   )					->					List[int]:
														'''simple docstring'''

														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 not None:
																					return [1] + ([0] * len(lowercase_   )) + [1] + ([0] * len(lowercase_   )) + [1]
														return [1] + ([0] * len(lowercase_   )) + [1]

							def      _lowercase       (		self			,			lowercase_			,			lowercase_ = None   )					->					List[int]:
														'''simple docstring'''

														lowerCAmelCase_										=     [self.sep_token_id]
														lowerCAmelCase_										=     [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      _lowercase       (		self			,			lowercase_			,			lowercase_ = None   )					->					Tuple[str]:
														'''simple docstring'''

														if not os.path.isdir(lowercase_   ):
																					logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''   )
																					return
														lowerCAmelCase_										=     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:
																												lowerCAmelCase_										=     self.sp_model.serialized_model_proto()
																												fi.write(lowercase_   )

														return (out_vocab_file,)



