



'''simple docstring'''

from __future__ import annotations

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

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






def 		_snake_case		(					_SCREAMING_SNAKE_CASE     :						str							,		_SCREAMING_SNAKE_CASE     :						Optional[Any]							)			->						list[str]:







	"""simple docstring"""
	lowerCAmelCase    =	{start}
	lowerCAmelCase    =	[start]
	lowerCAmelCase    =	Queue()
	queue.put(lowercase_							)
	while not queue.empty():
		lowerCAmelCase    =	queue.get()
		for w in graph[v]:
			if w not in explored:
				explored.add(lowercase_							)
				result.append(lowercase_							)
				queue.put(lowercase_							)
	return result






def 		_snake_case		(					_SCREAMING_SNAKE_CASE     :						int							,		_SCREAMING_SNAKE_CASE     :						str							)			->						list[str]:







	"""simple docstring"""
	lowerCAmelCase    =	{start}
	lowerCAmelCase    =	[start]
	lowerCAmelCase    =	deque([start]							)
	while queue:
		lowerCAmelCase    =	queue.popleft()
		for child in graph[v]:
			if child not in visited:
				visited.add(lowercase_							)
				result.append(lowercase_							)
				queue.append(lowercase_							)
	return result






def 		_snake_case		(					_SCREAMING_SNAKE_CASE     :						Optional[int]							)			->						None:







	"""simple docstring"""
	lowerCAmelCase    =	f'from __main__ import G, {name}'
	lowerCAmelCase    =	10_000
	lowerCAmelCase    =	timeit(f'{name}(G, \'A\')'							,		setup=lowercase_							,		number=lowercase_							)
	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






"""simple docstring"""


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

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


if is_sentencepiece_available():
  from .tokenization_reformer import ReformerTokenizer
else:
  lowerCamelCase__      =      None


lowerCamelCase__      =      logging.get_logger(__name__)


lowerCamelCase__      =      "▁"

lowerCamelCase__      =      {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase__      =      {
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    },
    "tokenizer_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json"
        )
    },
}

lowerCamelCase__      =      {
    "google/reformer-crime-and-punishment": 52_4288,
}



class    __SCREAMING_SNAKE_CASE			(  _UpperCamelCase      ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:List[str]		   =    VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__							:Any		   =    PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__							:List[Any]		   =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__							:List[Any]		   =    ["input_ids", "attention_mask"]
  SCREAMING_SNAKE_CASE__							:str		   =    ReformerTokenizer

  def __init__(						self      :				List[str]    ,      __a      :				str=None    ,      __a      :				List[Any]=None    ,      __a      :				Optional[int]="</s>"    ,      __a      :				str="<unk>"    ,      __a      :				Dict=[]    ,      **__a      :				Tuple    ,      )						-> Optional[int]:
        super().__init__(
            __a    ,      tokenizer_file=__a    ,      eos_token=__a    ,      unk_token=__a    ,      additional_special_tokens=__a    ,      **__a    ,      )

        _UpperCamelCase					:		Dict  =				vocab_file
        _UpperCamelCase					:		Optional[Any]  =				False if not self.vocab_file else True


  def       __SCREAMING_SNAKE_CASE (						self      :				Dict    ,      __a      :				str    ,      __a      :				Optional[str] = None		)						-> Tuple[str]:
        if not self.can_save_slow_tokenizer:
              raise ValueError(
                  "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                  "tokenizer."		)

        if not os.path.isdir(__a		):
              logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''		)
              return
        _UpperCamelCase					:		Optional[Any]  =				os.path.join(
            __a    ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

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

        return (out_vocab_file,)
