
"""simple docstring"""
class  _snake_case	:






							def __init__(       self    :      Dict     ):






												"""simple docstring"""



												__a:    Dict		     =       [0]
												__a:    str		     =       0






							def 				__lowercase	(       self    :      List[Any]    ,			snake_case__    :      int     ):






												"""simple docstring"""



												__a:    str		     =       self.__heap[i]
												while i // 2 > 0:
																	if self.__heap[i] > self.__heap[i // 2]:
																						__a:    Tuple		     =       self.__heap[i // 2]
																						__a:    Dict		     =       temporary
																	i //= 2






							def 				__lowercase	(       self    :      str    ,			snake_case__    :      int     ):






												"""simple docstring"""



												self.__heap.append(snake_case__     )
												self.__size += 1
												self.__swap_up(self.__size     )






							def 				__lowercase	(       self    :      int    ,			snake_case__    :      int     ):






												"""simple docstring"""



												while self.__size >= 2 * i:
																	if 2 * i + 1 > self.__size:
																						__a:    Any		     =       2 * i
																	else:
																						if self.__heap[2 * i] > self.__heap[2 * i + 1]:
																											__a:    Union[str, Any]		     =       2 * i
																						else:
																											__a:    Tuple		     =       2 * i + 1
																	__a:    int		     =       self.__heap[i]
																	if self.__heap[i] < self.__heap[bigger_child]:
																						__a:    int		     =       self.__heap[bigger_child]
																						__a:    Dict		     =       temporary
																	__a:    List[Any]		     =       bigger_child






							def 				__lowercase	(       self    :      Union[str, Any]     ):






												"""simple docstring"""



												__a:    Optional[Any]		     =       self.__heap[1]
												__a:    List[str]		     =       self.__heap[self.__size]
												self.__size -= 1
												self.__heap.pop()
												self.__swap_down(1     )
												return max_value






							@property
							def 				__lowercase	(       self    :      Optional[Any]     ):






												"""simple docstring"""



												return self.__heap[1:]






							def __len__(       self    :      str     ):






												"""simple docstring"""



												return self.__size


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			# create an instance of BinaryHeap
			lowercase		:    Optional[Any]			=       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))


"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase		:    Tuple			=       {
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    int			=       ['CodeGenTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       [
			    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CodeGenForCausalLM',
			    'CodeGenModel',
			    'CodeGenPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
			from .tokenization_codegen import CodeGenTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_codegen_fast import CodeGenTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_codegen import (
						    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CodeGenForCausalLM,
						    CodeGenModel,
						    CodeGenPreTrainedModel,
						)

else:
			import sys

			lowercase		:    Optional[Any]			=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
