



class       a					:

     '''simple docstring'''





     def __init__(     self       :      Optional[Any] ,   __snake_case       :      List[str] ,   __snake_case       :      str    ):
         UpperCAmelCase_										=					name
         UpperCAmelCase_										=					val
     def __str__(     self       :      List[Any]    ):
         return F'{self.__class__.__name__}({self.name}, {self.val})'




     def __lt__(     self       :      Dict ,   __snake_case       :      Optional[Any]    ):
         return self.val < other.val



class       a					:

     '''simple docstring'''





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

         for idx, i in enumerate(__snake_case    ):
             UpperCAmelCase_										=					idx
             UpperCAmelCase_										=					i.val

         for i in range(__snake_case ,   -1 ,   -1    ):
             self.sift_down(__snake_case ,   __snake_case    )
         return array
     def   lowerCamelCase_       (     self       :      Tuple ,   __snake_case       :      str ,   __snake_case       :      Tuple    ):
         while True:
             UpperCAmelCase_										=					self.get_left_child_idx(__snake_case    )  # noqa: E741
             UpperCAmelCase_										=					self.get_right_child_idx(__snake_case    )

             UpperCAmelCase_										=					idx
             if l < len(__snake_case    ) and array[l] < array[idx]:
                 UpperCAmelCase_										=					l
             if r < len(__snake_case    ) and array[r] < array[smallest]:
                 UpperCAmelCase_										=					r

             if smallest != idx:
                 UpperCAmelCase_			,							UpperCAmelCase_										=					array[smallest], array[idx]
                 (
                     (
                     UpperCAmelCase_							
                 )			,							(
                     UpperCAmelCase_							
                 )			,														
                 )										=					(
                     self.idx_of_element[array[smallest]],
                     self.idx_of_element[array[idx]],
                 )
                 UpperCAmelCase_										=					smallest
             else:
                 break
     def   lowerCamelCase_       (     self       :      int ,   __snake_case       :      List[Any]    ):
         UpperCAmelCase_										=					self.get_parent_idx(__snake_case    )
         while p >= 0 and self.heap[p] > self.heap[idx]:
             UpperCAmelCase_			,							UpperCAmelCase_										=					self.heap[idx], self.heap[p]
             UpperCAmelCase_			,							UpperCAmelCase_										=					(
                 self.idx_of_element[self.heap[idx]],
                 self.idx_of_element[self.heap[p]],
             )
             UpperCAmelCase_										=					p
             UpperCAmelCase_										=					self.get_parent_idx(__snake_case    )
     def   lowerCamelCase_       (     self       :      Union[str, Any]    ):
         return self.heap[0]
     def   lowerCamelCase_       (     self       :      Any    ):
         UpperCAmelCase_			,							UpperCAmelCase_										=					self.heap[-1], self.heap[0]
         UpperCAmelCase_			,							UpperCAmelCase_										=					(
             self.idx_of_element[self.heap[-1]],
             self.idx_of_element[self.heap[0]],
         )

         UpperCAmelCase_										=					self.heap.pop()
         del self.idx_of_element[x]
         self.sift_down(0 ,   self.heap    )
         return x
     def   lowerCamelCase_       (     self       :      Optional[int] ,   __snake_case       :      Tuple    ):
         self.heap.append(__snake_case    )
         UpperCAmelCase_										=					len(self.heap    ) - 1
         UpperCAmelCase_										=					node.val
         self.sift_up(len(self.heap    ) - 1    )
     def   lowerCamelCase_       (     self       :      Optional[Any]    ):
         return len(self.heap    ) == 0




     def   lowerCamelCase_       (     self       :      List[Any] ,   __snake_case       :      Any ,   __snake_case       :      Optional[int]    ):
         assert (
             self.heap[self.idx_of_element[node]].val > new_value
         ), "newValue must be less that current value"
         UpperCAmelCase_										=					new_value
         UpperCAmelCase_										=					new_value
         self.sift_up(self.idx_of_element[node]    )


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

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

# Generating Min-Heap from array
_lowerCamelCase      			=						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()











from typing import TYPE_CHECKING

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


_lowerCamelCase      			=						{
    'configuration_roberta': ['ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RobertaConfig', 'RobertaOnnxConfig'],
    'tokenization_roberta': ['RobertaTokenizer'],
}

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

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						[
     'ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
     'RobertaForCausalLM',
     'RobertaForMaskedLM',
     'RobertaForMultipleChoice',
     'RobertaForQuestionAnswering',
     'RobertaForSequenceClassification',
     'RobertaForTokenClassification',
     'RobertaModel',
     'RobertaPreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						[
     'TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFRobertaForCausalLM',
     'TFRobertaForMaskedLM',
     'TFRobertaForMultipleChoice',
     'TFRobertaForQuestionAnswering',
     'TFRobertaForSequenceClassification',
     'TFRobertaForTokenClassification',
     'TFRobertaMainLayer',
     'TFRobertaModel',
     'TFRobertaPreTrainedModel',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						[
     'FlaxRobertaForCausalLM',
     'FlaxRobertaForMaskedLM',
     'FlaxRobertaForMultipleChoice',
     'FlaxRobertaForQuestionAnswering',
     'FlaxRobertaForSequenceClassification',
     'FlaxRobertaForTokenClassification',
     'FlaxRobertaModel',
     'FlaxRobertaPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig, RobertaOnnxConfig
 from .tokenization_roberta import RobertaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_roberta_fast import RobertaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_roberta import (
      ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
      RobertaForCausalLM,
      RobertaForMaskedLM,
      RobertaForMultipleChoice,
      RobertaForQuestionAnswering,
      RobertaForSequenceClassification,
      RobertaForTokenClassification,
      RobertaModel,
      RobertaPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_roberta import (
      TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFRobertaForCausalLM,
      TFRobertaForMaskedLM,
      TFRobertaForMultipleChoice,
      TFRobertaForQuestionAnswering,
      TFRobertaForSequenceClassification,
      TFRobertaForTokenClassification,
      TFRobertaMainLayer,
      TFRobertaModel,
      TFRobertaPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_roberta import (
      FlaxRobertaForCausalLM,
      FlaxRobertaForMaskedLM,
      FlaxRobertaForMultipleChoice,
      FlaxRobertaForQuestionAnswering,
      FlaxRobertaForSequenceClassification,
      FlaxRobertaForTokenClassification,
      FlaxRobertaModel,
      FlaxRobertaPreTrainedModel,
  )

else:
 import sys

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





