
class 						UpperCamelCase__    :
   def __init__(self					:   Union[str, Any]   ,							snake_case_					:   Union[str, Any]   ,							snake_case_					:   List[Any]  ):
    __a					:    List[Any]													=    name
    __a					:    Optional[int]													=    val
   def __str__(self					:   Dict  ):
    return f"{self.__class__.__name__}({self.name}, {self.val})"







   def __lt__(self					:   Union[str, Any]   ,							snake_case_					:   List[str]  ):
    return self.val < other.val





class 						UpperCamelCase__    :
   def __init__(self					:   Optional[int]   ,							snake_case_					:   Union[str, Any]  ):
    __a					:    List[Any]													=    {}
    __a					:    List[Any]													=    {}
    __a					:    Union[str, Any]													=    self.build_heap(A_  )
   def __getitem__(self					:   str   ,							snake_case_					:   Dict  ):
    return self.get_value(A_  )
   def  lowerCAmelCase     (self					:   int   ,							snake_case_					:   Optional[int]  ):
    return (idx - 1) // 2
   def  lowerCAmelCase     (self					:   int   ,							snake_case_					:   Tuple  ):
    return idx * 2 + 1
   def  lowerCAmelCase     (self					:   int   ,							snake_case_					:   Any  ):
    return idx * 2 + 2
   def  lowerCAmelCase     (self					:   int   ,							snake_case_					:   Tuple  ):
    return self.heap_dict[key]
   def  lowerCAmelCase     (self					:   Tuple   ,							snake_case_					:   Any  ):
    __a					:    Optional[int]													=    len(A_  ) - 1
    __a					:    Dict													=    self.get_parent_idx(A_  )

    for idx, i in enumerate(A_  ):
     __a					:    Optional[Any]													=    idx
     __a					:    Union[str, Any]													=    i.val

    for i in range(A_   ,							-1   ,							-1  ):
     self.sift_down(A_   ,							A_  )
    return array
   def  lowerCAmelCase     (self					:   List[str]   ,							snake_case_					:   Union[str, Any]   ,							snake_case_					:   Tuple  ):
    while True:
     __a					:    Union[str, Any]													=    self.get_left_child_idx(A_  )  # noqa: E741
     __a					:    int													=    self.get_right_child_idx(A_  )

     __a					:    int													=    idx
     if l < len(A_  ) and array[l] < array[idx]:
      __a					:    Optional[int]													=    l
     if r < len(A_  ) and array[r] < array[smallest]:
      __a					:    Dict													=    r

     if smallest != idx:
      __a							,			__a					:    int													=    array[smallest], array[idx]
      (
          (
          __a   
      )							,			(
          __a   
      )							,			   
      )					:    str													=    (
          self.idx_of_element[array[smallest]],
          self.idx_of_element[array[idx]],
      )
      __a					:    Tuple													=    smallest
     else:
      break
   def  lowerCAmelCase     (self					:   List[Any]   ,							snake_case_					:   Any  ):
    __a					:    Tuple													=    self.get_parent_idx(A_  )
    while p >= 0 and self.heap[p] > self.heap[idx]:
     __a							,			__a					:    Any													=    self.heap[idx], self.heap[p]
     __a							,			__a					:    Optional[int]													=    (
         self.idx_of_element[self.heap[idx]],
         self.idx_of_element[self.heap[p]],
     )
     __a					:    Optional[int]													=    p
     __a					:    List[str]													=    self.get_parent_idx(A_  )
   def  lowerCAmelCase     (self					:   Optional[Any]  ):
    return self.heap[0]
   def  lowerCAmelCase     (self					:   List[str]  ):
    __a							,			__a					:    Any													=    self.heap[-1], self.heap[0]
    __a							,			__a					:    List[Any]													=    (
        self.idx_of_element[self.heap[-1]],
        self.idx_of_element[self.heap[0]],
    )

    __a					:    int													=    self.heap.pop()
    del self.idx_of_element[x]
    self.sift_down(0   ,							self.heap  )
    return x
   def  lowerCAmelCase     (self					:   List[Any]   ,							snake_case_					:   Optional[int]  ):
    self.heap.append(A_  )
    __a					:    List[Any]													=    len(self.heap  ) - 1
    __a					:    List[str]													=    node.val
    self.sift_up(len(self.heap  ) - 1  )
   def  lowerCAmelCase     (self					:   Union[str, Any]  ):
    return len(self.heap  ) == 0







   def  lowerCAmelCase     (self					:   int   ,							snake_case_					:   Union[str, Any]   ,							snake_case_					:   Optional[int]  ):
    assert (
        self.heap[self.idx_of_element[node]].val > new_value
    ), "newValue must be less that current value"
    __a					:    str													=    new_value
    __a					:    Tuple													=    new_value
    self.sift_up(self.idx_of_element[node]  )





lowercase__         =Node('R', -1)
lowercase__         =Node('B', 6)
lowercase__         =Node('A', 3)
lowercase__         =Node('X', 1)
lowercase__         =Node('E', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
lowercase__         =MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('Min Heap - before decrease key')
for i in my_min_heap.heap:
      print(i)

print('Min Heap - After decrease key of node [B -> -17]')
my_min_heap.decrease_key(b, -17)

# After
for i in my_min_heap.heap:
      print(i)

if __name__ == "__main__":
      import doctest

      doctest.testmod()


"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowercase				 =					{
    '''configuration_electra''': ['''ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ElectraConfig''', '''ElectraOnnxConfig'''],
    '''tokenization_electra''': ['''ElectraTokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase				 =					['''ElectraTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase				 =					[
		    '''ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ElectraForCausalLM''',
		    '''ElectraForMaskedLM''',
		    '''ElectraForMultipleChoice''',
		    '''ElectraForPreTraining''',
		    '''ElectraForQuestionAnswering''',
		    '''ElectraForSequenceClassification''',
		    '''ElectraForTokenClassification''',
		    '''ElectraModel''',
		    '''ElectraPreTrainedModel''',
		    '''load_tf_weights_in_electra''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase				 =					[
		    '''TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFElectraForMaskedLM''',
		    '''TFElectraForMultipleChoice''',
		    '''TFElectraForPreTraining''',
		    '''TFElectraForQuestionAnswering''',
		    '''TFElectraForSequenceClassification''',
		    '''TFElectraForTokenClassification''',
		    '''TFElectraModel''',
		    '''TFElectraPreTrainedModel''',
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase				 =					[
		    '''FlaxElectraForCausalLM''',
		    '''FlaxElectraForMaskedLM''',
		    '''FlaxElectraForMultipleChoice''',
		    '''FlaxElectraForPreTraining''',
		    '''FlaxElectraForQuestionAnswering''',
		    '''FlaxElectraForSequenceClassification''',
		    '''FlaxElectraForTokenClassification''',
		    '''FlaxElectraModel''',
		    '''FlaxElectraPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
		from .tokenization_electra import ElectraTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_electra_fast import ElectraTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_electra import (
				    ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ElectraForCausalLM,
				    ElectraForMaskedLM,
				    ElectraForMultipleChoice,
				    ElectraForPreTraining,
				    ElectraForQuestionAnswering,
				    ElectraForSequenceClassification,
				    ElectraForTokenClassification,
				    ElectraModel,
				    ElectraPreTrainedModel,
				    load_tf_weights_in_electra,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_electra import (
				    TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFElectraForMaskedLM,
				    TFElectraForMultipleChoice,
				    TFElectraForPreTraining,
				    TFElectraForQuestionAnswering,
				    TFElectraForSequenceClassification,
				    TFElectraForTokenClassification,
				    TFElectraModel,
				    TFElectraPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_electra import (
				    FlaxElectraForCausalLM,
				    FlaxElectraForMaskedLM,
				    FlaxElectraForMultipleChoice,
				    FlaxElectraForPreTraining,
				    FlaxElectraForQuestionAnswering,
				    FlaxElectraForSequenceClassification,
				    FlaxElectraForTokenClassification,
				    FlaxElectraModel,
				    FlaxElectraPreTrainedModel,
				)

else:
		import sys

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