
"""simple docstring"""







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:
		_SCREAMING_SNAKE_CASE	       =      None

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

_SCREAMING_SNAKE_CASE	       =      {
    """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""",
    },
}

_SCREAMING_SNAKE_CASE	       =      {
    """google/fnet-base""": 512,
    """google/fnet-large""": 512,
}

_SCREAMING_SNAKE_CASE	       =      """▁"""







class 							__magic_name__     (		lowercase__   ):
					_SCREAMING_SNAKE_CASE       :					Any     							=   VOCAB_FILES_NAMES
					_SCREAMING_SNAKE_CASE       :					Optional[Any]     							=   PRETRAINED_VOCAB_FILES_MAP
					_SCREAMING_SNAKE_CASE       :					Any     							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_SCREAMING_SNAKE_CASE       :					Any     							=   ['input_ids', 'token_type_ids']
					_SCREAMING_SNAKE_CASE       :					Optional[int]     							=   FNetTokenizer





					def __init__(				self   :							Dict							,						snake_case_   :							List[Any]=None							,						snake_case_   :							List[str]=None							,						snake_case_   :							Tuple=False							,						snake_case_   :							Tuple=True							,						snake_case_   :							str=True							,						snake_case_   :							Tuple="<unk>"							,						snake_case_   :							List[str]="[SEP]"							,						snake_case_   :							Tuple="<pad>"							,						snake_case_   :							Any="[CLS]"							,						snake_case_   :							int="[MASK]"							,						**snake_case_   :							str							,						):
												# 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.
												__snake_case     			=       (
												    AddedToken(snake_case_							,						lstrip=snake_case_							,						rstrip=snake_case_							,						normalized=snake_case_    )
												    if isinstance(snake_case_							,						snake_case_    )
												    else mask_token
												)

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

												__snake_case     			=       do_lower_case
												__snake_case     			=       remove_space
												__snake_case     			=       keep_accents
												__snake_case     			=       vocab_file
												__snake_case     			=       False if not self.vocab_file else True





					def 							lowerCAmelCase      (				self   :							Tuple							,						snake_case_   :							List[int]							,						snake_case_   :							Optional[List[int]] = None    ):
												__snake_case     			=       [self.sep_token_id]
												__snake_case     			=       [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   :							List[Any]							,						snake_case_   :							List[int]							,						snake_case_   :							Optional[List[int]] = None    ):
												__snake_case     			=       [self.sep_token_id]
												__snake_case     			=       [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   :							int							,						snake_case_   :							str							,						snake_case_   :							Optional[str] = None    ):
												if not os.path.isdir(snake_case_    ):
																			logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''    )
																			return
												__snake_case     			=       os.path.join(
												    snake_case_							,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]    )

												if os.path.abspath(self.vocab_file    ) != os.path.abspath(snake_case_    ):
																			copyfile(self.vocab_file							,						snake_case_    )

												return (out_vocab_file,)


"""simple docstring"""







from __future__ import annotations

from itertools import permutations
from random import randint
from timeit import repeat
def   __UpperCamelCase   (					)  ->     tuple[list[int], int]:







							"""simple docstring"""


							__snake_case     			=       [randint(-10_00							,    10_00 ) for i in range(10 )]
							__snake_case     			=       randint(-50_00							,    50_00 )
							return (arr, r)


_SCREAMING_SNAKE_CASE	       =      make_dataset()
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     tuple[int, ...]:







							"""simple docstring"""


							for triplet in permutations(SCREAMING_SNAKE_CASE							,    3 ):
														if sum(SCREAMING_SNAKE_CASE ) == target:
																					return tuple(sorted(SCREAMING_SNAKE_CASE ) )
							return (0, 0, 0)
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     tuple[int, int, int]:







							"""simple docstring"""


							arr.sort()
							__snake_case     			=       len(SCREAMING_SNAKE_CASE )
							for i in range(n - 1 ):
														__snake_case			,   __snake_case     			=       i + 1, n - 1
														while left < right:
																					if arr[i] + arr[left] + arr[right] == target:
																												return (arr[i], arr[left], arr[right])
																					elif arr[i] + arr[left] + arr[right] < target:
																												left += 1
																					elif arr[i] + arr[left] + arr[right] > target:
																												right -= 1
							return (0, 0, 0)
def   __UpperCamelCase   (					)  ->     tuple[float, float]:







							"""simple docstring"""


							__snake_case     			=       "\nfrom __main__ import dataset, triplet_sum1, triplet_sum2\n"
							__snake_case     			=       "\ntriplet_sum1(*dataset)\n"
							__snake_case     			=       "\ntriplet_sum2(*dataset)\n"
							__snake_case     			=       repeat(setup=SCREAMING_SNAKE_CASE							,    stmt=SCREAMING_SNAKE_CASE							,    repeat=5							,    number=1_00_00 )
							__snake_case     			=       repeat(setup=SCREAMING_SNAKE_CASE							,    stmt=SCREAMING_SNAKE_CASE							,    repeat=5							,    number=1_00_00 )
							return (min(SCREAMING_SNAKE_CASE ), min(SCREAMING_SNAKE_CASE ))


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

		testmod()
		_SCREAMING_SNAKE_CASE	       =      solution_times()
		print(F"""The time for naive implementation is {times[0]}.""")
		print(F"""The time for optimized implementation is {times[1]}.""")
