from typing import TYPE_CHECKING

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


lowerCAmelCase__							= {
    'configuration_imagegpt': ['IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ImageGPTConfig', 'ImageGPTOnnxConfig']
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= ['ImageGPTFeatureExtractor']
    lowerCAmelCase__							= ['ImageGPTImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= [
        'IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ImageGPTForCausalImageModeling',
        'ImageGPTForImageClassification',
        'ImageGPTModel',
        'ImageGPTPreTrainedModel',
        'load_tf_weights_in_imagegpt',
    ]


if TYPE_CHECKING:
    from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
        from .image_processing_imagegpt import ImageGPTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_imagegpt import (
            IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
            ImageGPTForCausalImageModeling,
            ImageGPTForImageClassification,
            ImageGPTModel,
            ImageGPTPreTrainedModel,
            load_tf_weights_in_imagegpt,
        )

else:
    import sys

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



class 		__magic_name__ :






     def __init__(							self     )->			int:
         UpperCamelCase_          =		[0]
         UpperCamelCase_          =		0






     def      UpperCAmelCase_							(							self						,		_lowercase     )->			None:
         UpperCamelCase_          =		self.__heap[i]
         while i // 2 > 0:
             if self.__heap[i] > self.__heap[i // 2]:
                 UpperCamelCase_          =		self.__heap[i // 2]
                 UpperCamelCase_          =		temporary
             i //= 2






     def      UpperCAmelCase_							(							self						,		_lowercase     )->			None:
         self.__heap.append(_lowercase     )
         self.__size += 1
         self.__swap_up(self.__size     )






     def      UpperCAmelCase_							(							self						,		_lowercase     )->			None:
         while self.__size >= 2 * i:
             if 2 * i + 1 > self.__size:
                 UpperCamelCase_          =		2 * i
             else:
                 if self.__heap[2 * i] > self.__heap[2 * i + 1]:
                     UpperCamelCase_          =		2 * i
                 else:
                     UpperCamelCase_          =		2 * i + 1
             UpperCamelCase_          =		self.__heap[i]
             if self.__heap[i] < self.__heap[bigger_child]:
                 UpperCamelCase_          =		self.__heap[bigger_child]
                 UpperCamelCase_          =		temporary
             UpperCamelCase_          =		bigger_child






     def      UpperCAmelCase_							(							self     )->			int:
         UpperCamelCase_          =		self.__heap[1]
         UpperCamelCase_          =		self.__heap[self.__size]
         self.__size -= 1
         self.__heap.pop()
         self.__swap_down(1     )
         return max_value






     @property
     def      UpperCAmelCase_							(							self     )->			List[Any]:
         return self.__heap[1:]






     def __len__(							self     )->			List[str]:
         return self.__size


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 # create an instance of BinaryHeap
 SCREAMING_SNAKE_CASE						:Optional[int]      =			BinaryHeap()
 binary_heap.insert(6)
 binary_heap.insert(10)
 binary_heap.insert(15)
 binary_heap.insert(12)
 # pop root(max-values because it is max heap)
 print(binary_heap.pop())  # 15
 print(binary_heap.pop())  # 12
 # get the list and size after operations
 print(binary_heap.get_list)
 print(len(binary_heap))
