






"""simple docstring"""

from collections.abc import Callable





class    lowerCamelCase__						:
      def __init__(		self	:	str      ,       A_	:	Callable | None = None							):






       '''simple docstring'''


       __lowercase									=	[]
       # Stores indexes of each item for supporting updates and deletion.
       __lowercase									=	{}
       # Stores current size of heap.
       __lowercase									=	0
       # Stores function used to evaluate the score of an item on which basis ordering
       # will be done.
       __lowercase									=	key or (lambda A_							: x)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]      ,       A_	:	int							):






       '''simple docstring'''


       return int((i - 1) / 2							) if i > 0 else None
      def SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	int(2 * i + 1							)
       return left if 0 < left < self.size else None
      def SCREAMING_SNAKE_CASE_	(		self	:	int      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	int(2 * i + 2							)
       return right if 0 < right < self.size else None
      def SCREAMING_SNAKE_CASE_	(		self	:	int      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase							,		__lowercase									=	(
           self.pos_map[self.arr[j][0]],
           self.pos_map[self.arr[i][0]],
       )
       # Then swap the items in the list.
       __lowercase							,		__lowercase									=	self.arr[j], self.arr[i]
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       return self.arr[i][1] < self.arr[j][1]
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	self._left(A_							)
       __lowercase									=	self._right(A_							)
       __lowercase									=	i

       if left is not None and not self._cmp(A_      ,       A_							):
        __lowercase									=	left
       if right is not None and not self._cmp(A_      ,       A_							):
        __lowercase									=	right

       return valid_parent
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	self._parent(A_							)
       while parent is not None and not self._cmp(A_      ,       A_							):
        self._swap(A_      ,       A_							)
        __lowercase							,		__lowercase									=	parent, self._parent(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	self._get_valid_parent(A_							)
       while valid_parent != index:
        self._swap(A_      ,       A_							)
        __lowercase							,		__lowercase									=	valid_parent, self._get_valid_parent(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Any      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       if item not in self.pos_map:
        return
       __lowercase									=	self.pos_map[item]
       __lowercase									=	[item, self.key(A_							)]
       # Make sure heap is right in both up and down direction.
       # Ideally only one of them will make any change.
       self._heapify_up(A_							)
       self._heapify_down(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	str      ,       A_	:	int							):






       '''simple docstring'''


       if item not in self.pos_map:
        return
       __lowercase									=	self.pos_map[item]
       del self.pos_map[item]
       __lowercase									=	self.arr[self.size - 1]
       __lowercase									=	index
       self.size -= 1
       # Make sure heap is right in both up and down direction. Ideally only one
       # of them will make any change- so no performance loss in calling both.
       if self.size > index:
        self._heapify_up(A_							)
        self._heapify_down(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	len(self.arr							)
       if arr_len == self.size:
        self.arr.append([item, self.key(A_							)]							)
       else:
        __lowercase									=	[item, self.key(A_							)]
       __lowercase									=	self.size
       self.size += 1
       self._heapify_up(self.size - 1							)
      def SCREAMING_SNAKE_CASE_	(		self	:	str							):






       '''simple docstring'''


       return self.arr[0] if self.size else None






      def SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       __lowercase									=	self.get_top()
       if top_item_tuple:
        self.delete_item(top_item_tuple[0]							)
       return top_item_tuple






def lowerCAmelCase_      (				):






 """simple docstring"""
















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


UpperCAmelCase__  							={
    "configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioConfig"],
    "configuration_data2vec_text": [
        "DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Data2VecTextConfig",
        "Data2VecTextOnnxConfig",
    ],
    "configuration_data2vec_vision": [
        "DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Data2VecVisionConfig",
        "Data2VecVisionOnnxConfig",
    ],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase__  							=[
           "DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST",
           "Data2VecAudioForAudioFrameClassification",
           "Data2VecAudioForCTC",
           "Data2VecAudioForSequenceClassification",
           "Data2VecAudioForXVector",
           "Data2VecAudioModel",
           "Data2VecAudioPreTrainedModel",
       ]
       UpperCAmelCase__  							=[
           "DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "Data2VecTextForCausalLM",
           "Data2VecTextForMaskedLM",
           "Data2VecTextForMultipleChoice",
           "Data2VecTextForQuestionAnswering",
           "Data2VecTextForSequenceClassification",
           "Data2VecTextForTokenClassification",
           "Data2VecTextModel",
           "Data2VecTextPreTrainedModel",
       ]
       UpperCAmelCase__  							=[
           "DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST",
           "Data2VecVisionForImageClassification",
           "Data2VecVisionForMaskedImageModeling",
           "Data2VecVisionForSemanticSegmentation",
           "Data2VecVisionModel",
           "Data2VecVisionPreTrainedModel",
       ]

if is_tf_available():
       UpperCAmelCase__  							=[
           "TFData2VecVisionForImageClassification",
           "TFData2VecVisionForSemanticSegmentation",
           "TFData2VecVisionModel",
           "TFData2VecVisionPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
       from .configuration_dataavec_text import (
           DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           DataaVecTextConfig,
           DataaVecTextOnnxConfig,
       )
       from .configuration_dataavec_vision import (
           DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
           DataaVecVisionConfig,
           DataaVecVisionOnnxConfig,
       )

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_dataavec_audio import (
                  DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DataaVecAudioForAudioFrameClassification,
                  DataaVecAudioForCTC,
                  DataaVecAudioForSequenceClassification,
                  DataaVecAudioForXVector,
                  DataaVecAudioModel,
                  DataaVecAudioPreTrainedModel,
              )
              from .modeling_dataavec_text import (
                  DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DataaVecTextForCausalLM,
                  DataaVecTextForMaskedLM,
                  DataaVecTextForMultipleChoice,
                  DataaVecTextForQuestionAnswering,
                  DataaVecTextForSequenceClassification,
                  DataaVecTextForTokenClassification,
                  DataaVecTextModel,
                  DataaVecTextPreTrainedModel,
              )
              from .modeling_dataavec_vision import (
                  DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DataaVecVisionForImageClassification,
                  DataaVecVisionForMaskedImageModeling,
                  DataaVecVisionForSemanticSegmentation,
                  DataaVecVisionModel,
                  DataaVecVisionPreTrainedModel,
              )
       if is_tf_available():
              from .modeling_tf_dataavec_vision import (
                  TFDataaVecVisionForImageClassification,
                  TFDataaVecVisionForSemanticSegmentation,
                  TFDataaVecVisionModel,
                  TFDataaVecVisionPreTrainedModel,
              )

else:
       import sys

       UpperCAmelCase__  							=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
