
class 			lowercase__:



	"""simple docstring"""




	def __init__(	self  :      int	)	->					None:
					lowercase_					  = {}
					# indexmap keys are an index and it's values are the number at that index
					lowercase_					  = {}
	def 						_lowercase  (	self  :      Any	,							SCREAMING_SNAKE_CASE_  :      List[str]	,							SCREAMING_SNAKE_CASE_  :      List[str]	)	->					list[int]:







					if isinstance(lowercase__	,							(range, str)	):
									lowercase_					  = list(lowercase__	)
					elif not isinstance(lowercase__	,							lowercase__	):
									raise TypeError(
									    '''binary_search_delete() only accepts either a list, range or str'''	)

					lowercase_					  = 0
					lowercase_					  = len(lowercase__	) - 1

					while low <= high:
									lowercase_					  = (low + high) // 2
									if array[mid] == item:
													array.pop(lowercase__	)
													return array
									elif array[mid] < item:
													lowercase_					  = mid + 1
									else:
													lowercase_					  = mid - 1
					raise ValueError(
					    '''Either the item is not in the array or the array was unsorted'''	)
	def 						_lowercase  (	self  :      str	,							SCREAMING_SNAKE_CASE_  :      Any	,							SCREAMING_SNAKE_CASE_  :      Dict	)	->					list[int]:







					if isinstance(lowercase__	,							(range, str)	):
									lowercase_					  = list(lowercase__	)
					elif not isinstance(lowercase__	,							lowercase__	):
									raise TypeError(
									    '''binary_search_insert() only accepts either a list, range or str'''	)

					lowercase_					  = 0
					lowercase_					  = len(lowercase__	) - 1

					while low <= high:
									lowercase_					  = (low + high) // 2
									if array[mid] == index:
													# If the item already exists in the array,
													# insert it after the existing item
													array.insert(mid + 1	,							lowercase__	)
													return array
									elif array[mid] < index:
													lowercase_					  = mid + 1
									else:
													lowercase_					  = mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
					array.insert(lowercase__	,							lowercase__	)
					return array
	def 						_lowercase  (	self  :      Optional[int]	,							SCREAMING_SNAKE_CASE_  :      Optional[Any]	,							SCREAMING_SNAKE_CASE_  :      Any	)	->					None:







					if index in self.indexmap:
									lowercase_					  = self.indexmap[index]
									if len(self.numbermap[n]	) == 1:
													del self.numbermap[n]
									else:
													lowercase_					  = self.binary_search_delete(self.numbermap[n]	,							lowercase__	)

        # Set new index
					lowercase_					  = number

					# Number not seen before or empty so insert number value
					if number not in self.numbermap:
									lowercase_					  = [index]

					# Here we need to perform a binary search insertion in order to insert
					# The item in the correct place
					else:
									lowercase_					  = self.binary_search_insert(
									    self.numbermap[number]	,							lowercase__	)




	def 						_lowercase  (	self  :      str	,							SCREAMING_SNAKE_CASE_  :      str	)	->					int:
					return self.numbermap.get(lowercase__	,							[-1]	)[0]


if __name__ == "__main__":
							import doctest

							doctest.testmod()






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__a        = {
    'configuration_nystromformer': ['NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NystromformerConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a        = [
						    'NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'NystromformerForMaskedLM',
						    'NystromformerForMultipleChoice',
						    'NystromformerForQuestionAnswering',
						    'NystromformerForSequenceClassification',
						    'NystromformerForTokenClassification',
						    'NystromformerLayer',
						    'NystromformerModel',
						    'NystromformerPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_nystromformer import (
												    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    NystromformerForMaskedLM,
												    NystromformerForMultipleChoice,
												    NystromformerForQuestionAnswering,
												    NystromformerForSequenceClassification,
												    NystromformerForTokenClassification,
												    NystromformerLayer,
												    NystromformerModel,
												    NystromformerPreTrainedModel,
												)


else:
						import sys

						__a        = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




