
class       A__  :





							def __init__(					self    :  str							)		->						int:



											"""simple docstring"""


											__lowercase								=   [0]
											__lowercase								=   0





							def      a__					(					self    :  List[Any]	,					_UpperCAmelCase    :  int							)		->						None:



											"""simple docstring"""


											__lowercase								=   self.__heap[i]
											while i // 2 > 0:
															if self.__heap[i] > self.__heap[i // 2]:
																			__lowercase								=   self.__heap[i // 2]
																			__lowercase								=   temporary
															i //= 2





							def      a__					(					self    :  Optional[int]	,					_UpperCAmelCase    :  int							)		->						None:



											"""simple docstring"""


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





							def      a__					(					self    :  Tuple	,					_UpperCAmelCase    :  int							)		->						None:



											"""simple docstring"""


											while self.__size >= 2 * i:
															if 2 * i + 1 > self.__size:
																			__lowercase								=   2 * i
															else:
																			if self.__heap[2 * i] > self.__heap[2 * i + 1]:
																							__lowercase								=   2 * i
																			else:
																							__lowercase								=   2 * i + 1
															__lowercase								=   self.__heap[i]
															if self.__heap[i] < self.__heap[bigger_child]:
																			__lowercase								=   self.__heap[bigger_child]
																			__lowercase								=   temporary
															__lowercase								=   bigger_child





							def      a__					(					self    :  List[Any]							)		->						int:



											"""simple docstring"""


											__lowercase								=   self.__heap[1]
											__lowercase								=   self.__heap[self.__size]
											self.__size -= 1
											self.__heap.pop()
											self.__swap_down(1							)
											return max_value





							@property
							def      a__					(					self    :  Tuple							)		->						Tuple:



											"""simple docstring"""


											return self.__heap[1:]





							def __len__(					self    :  List[str]							)		->						Any:



											"""simple docstring"""


											return self.__size


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							# create an instance of BinaryHeap
							SCREAMING_SNAKE_CASE__				=							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))







# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__				=							{
    """agents""": ["""Agent""", """AzureOpenAiAgent""", """HfAgent""", """LocalAgent""", """OpenAiAgent"""],
    """base""": ["""PipelineTool""", """RemoteTool""", """Tool""", """launch_gradio_demo""", """load_tool"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__				=							["""DocumentQuestionAnsweringTool"""]
							SCREAMING_SNAKE_CASE__				=							["""ImageCaptioningTool"""]
							SCREAMING_SNAKE_CASE__				=							["""ImageQuestionAnsweringTool"""]
							SCREAMING_SNAKE_CASE__				=							["""ImageSegmentationTool"""]
							SCREAMING_SNAKE_CASE__				=							["""SpeechToTextTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextClassificationTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextQuestionAnsweringTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextSummarizationTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextToSpeechTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TranslationTool"""]

if TYPE_CHECKING:
							from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
							from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .document_question_answering import DocumentQuestionAnsweringTool
														from .image_captioning import ImageCaptioningTool
														from .image_question_answering import ImageQuestionAnsweringTool
														from .image_segmentation import ImageSegmentationTool
														from .speech_to_text import SpeechToTextTool
														from .text_classification import TextClassificationTool
														from .text_question_answering import TextQuestionAnsweringTool
														from .text_summarization import TextSummarizationTool
														from .text_to_speech import TextToSpeechTool
														from .translation import TranslationTool
else:
							import sys

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





