





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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_fnet import FNetTokenizer
else:
		A 			=  None

A 			=  logging.get_logger(__name__)
A 			=  {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

A 			=  {
    '''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''',
    },
    '''tokenizer_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json''',
    },
}

A 			=  {
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

A 			=  '''▁'''




class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  VOCAB_FILES_NAMES
					__lowerCAmelCase  =  PRETRAINED_VOCAB_FILES_MAP
					__lowerCAmelCase  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__lowerCAmelCase  =  ['''input_ids''', '''token_type_ids''']
					__lowerCAmelCase  =  FNetTokenizer







					def __init__(						self	,			_UpperCAmelCase=None	,			_UpperCAmelCase=None	,			_UpperCAmelCase=False	,			_UpperCAmelCase=True	,			_UpperCAmelCase=True	,			_UpperCAmelCase="<unk>"	,			_UpperCAmelCase="[SEP]"	,			_UpperCAmelCase="<pad>"	,			_UpperCAmelCase="[CLS]"	,			_UpperCAmelCase="[MASK]"	,			**_UpperCAmelCase	,			):
									# Mask token behave like a normal word, i.e. include the space before it and
									# is included in the raw text, there should be a match in a non-normalized sentence.
									__a :						List[str]			       =  (
									    AddedToken(_UpperCAmelCase	,			lstrip=_UpperCAmelCase	,			rstrip=_UpperCAmelCase	,			normalized=_UpperCAmelCase     )
									    if isinstance(_UpperCAmelCase	,			_UpperCAmelCase     )
									    else mask_token
									)

									super().__init__(
									    _UpperCAmelCase	,			tokenizer_file=_UpperCAmelCase	,			do_lower_case=_UpperCAmelCase	,			remove_space=_UpperCAmelCase	,			keep_accents=_UpperCAmelCase	,			unk_token=_UpperCAmelCase	,			sep_token=_UpperCAmelCase	,			pad_token=_UpperCAmelCase	,			cls_token=_UpperCAmelCase	,			mask_token=_UpperCAmelCase	,			**_UpperCAmelCase	,			)

									__a :						List[str]			       =  do_lower_case
									__a :						str			       =  remove_space
									__a :						Tuple			       =  keep_accents
									__a :						str			       =  vocab_file
									__a :						Dict			       =  False if not self.vocab_file else True







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase = None     ):
									__a :						int			       =  [self.sep_token_id]
									__a :						List[str]			       =  [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  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase = None     ):
									__a :						Optional[int]			       =  [self.sep_token_id]
									__a :						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     ) * [0] + len(token_ids_a + sep     ) * [1]







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase = None     ):
									if not os.path.isdir(_UpperCAmelCase     ):
													logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""     )
													return
									__a :						Optional[int]			       =  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     ):
													copyfile(self.vocab_file	,			_UpperCAmelCase     )

									return (out_vocab_file,)






"""simple docstring"""






from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass




@dataclass
class 				__lowercase			:







					'''simple docstring'''




					__lowerCAmelCase  =  42
					__lowerCAmelCase  =  42






class 				__lowercase			:







					'''simple docstring'''




					def __init__(						self	,			_UpperCAmelCase     ):
									__a :						list[list[Edge]]			       =  [[] for _ in range(_UpperCAmelCase     )]
									__a :						Dict			       =  size







					def __getitem__(						self	,			_UpperCAmelCase     ):
									return iter(self._graph[vertex]     )







					@property
					def  _lowerCamelCase		(						self     ):
									return self._size







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									if weight not in (0, 1):
													raise ValueError('''Edge weight must be either 0 or 1.'''     )

									if to_vertex < 0 or to_vertex >= self.size:
													raise ValueError('''Vertex indexes must be in [0; size).'''     )

									self._graph[from_vertex].append(Edge(_UpperCAmelCase	,			_UpperCAmelCase     )     )







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									__a :						List[str]			       =  deque([start_vertex]     )
									__a :						list[int | None]			       =  [None] * self.size
									__a :						int			       =  0

									while queue:
													__a :						Any			       =  queue.popleft()
													__a :						Tuple			       =  distances[current_vertex]
													if current_distance is None:
																	continue

													for edge in self[current_vertex]:
																	__a :						List[str]			       =  current_distance + edge.weight
																	__a :						str			       =  distances[edge.destination_vertex]
																	if (
																	    isinstance(_UpperCAmelCase	,			_UpperCAmelCase     )
																	    and new_distance >= dest_vertex_distance
																	):
																					continue
																	__a :						str			       =  new_distance
																	if edge.weight == 0:
																					queue.appendleft(edge.destination_vertex     )
																	else:
																					queue.append(edge.destination_vertex     )

									if distances[finish_vertex] is None:
													raise ValueError('''No path from start_vertex to finish_vertex.'''     )

									return distances[finish_vertex]


if __name__ == "__main__":
		import doctest

		doctest.testmod()