


'''simple docstring'''



class        UpperCAmelCase_  :





				"""simple docstring"""






				def __init__(							self     )    ->					Optional[int]:
									# numbermap keys are the number and its values are lists of indexes sorted
									# in ascending order
									__lowerCamelCase       :     dict[int, list[int]]        =		{}
									# indexmap keys are an index and it's values are the number at that index
									__lowerCamelCase       :     dict[int, int]        =		{}







				def 				lowercase_    (							self      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_     )    ->					Dict:
									if isinstance(_A      ,					(range, str)     ):
														__lowerCamelCase       :     Tuple        =		list(_A     )
									elif not isinstance(_A      ,					_A     ):
														raise TypeError(
														    'binary_search_delete() only accepts either a list, range or str'     )

									__lowerCamelCase       :     Optional[int]        =		0
									__lowerCamelCase       :     int        =		len(_A     ) - 1

									while low <= high:
														__lowerCamelCase       :     List[str]        =		(low + high) // 2
														if array[mid] == item:
																			array.pop(_A     )
																			return array
														elif array[mid] < item:
																			__lowerCamelCase       :     Union[str, Any]        =		mid + 1
														else:
																			__lowerCamelCase       :     str        =		mid - 1
									raise ValueError(
									    'Either the item is not in the array or the array was unsorted'     )







				def 				lowercase_    (							self      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_     )    ->					Union[str, Any]:
									if isinstance(_A      ,					(range, str)     ):
														__lowerCamelCase       :     int        =		list(_A     )
									elif not isinstance(_A      ,					_A     ):
														raise TypeError(
														    'binary_search_insert() only accepts either a list, range or str'     )

									__lowerCamelCase       :     List[str]        =		0
									__lowerCamelCase       :     int        =		len(_A     ) - 1

									while low <= high:
														__lowerCamelCase       :     List[Any]        =		(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      ,					_A     )
																			return array
														elif array[mid] < index:
																			__lowerCamelCase       :     Dict        =		mid + 1
														else:
																			__lowerCamelCase       :     Any        =		mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
									array.insert(_A      ,					_A     )
									return array







				def 				lowercase_    (							self      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_     )    ->					Any:
									# Remove previous index
									if index in self.indexmap:
														__lowerCamelCase       :     Any        =		self.indexmap[index]
														if len(self.numbermap[n]     ) == 1:
																			del self.numbermap[n]
														else:
																			__lowerCamelCase       :     Optional[int]        =		self.binary_search_delete(self.numbermap[n]      ,					_A     )

        # Set new index
									__lowerCamelCase       :     str        =		number

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

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







				def 				lowercase_    (							self      ,					SCREAMING_SNAKE_CASE_     )    ->					Any:
									return self.numbermap.get(_A      ,					[-1]     )[0]


if __name__ == "__main__":
						import doctest

						doctest.testmod()










'''simple docstring'''



from typing import TYPE_CHECKING

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


A__		: str												=  {"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		: List[str]												=  [
          """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """HubertForCTC""",
          """HubertForSequenceClassification""",
          """HubertModel""",
          """HubertPreTrainedModel""",
      ]


try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		: Optional[int]												=  [
          """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFHubertForCTC""",
          """TFHubertModel""",
          """TFHubertPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_hubert import (
                HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                HubertForCTC,
                HubertForSequenceClassification,
                HubertModel,
                HubertPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_hubert import (
                TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFHubertForCTC,
                TFHubertModel,
                TFHubertPreTrainedModel,
            )


else:
      import sys

      A__		: Optional[int]												=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






