"""simple docstring"""







class 						UpperCamelCase     :



				def __init__(self							: Union[str, Any]      ,    _A							: Union[str, Any])       ->      None:
					__snake_case     :				int 						=					data
					__snake_case     :				int
					__snake_case     :				Node







def     __UpperCAmelCase							(       UpperCAmelCase_       :							str    )				->     None:

	'''simple docstring'''





	__snake_case     :				Dict 						=					0
	__snake_case     :				Optional[Any] 						=					x
def     __UpperCAmelCase							(       UpperCAmelCase_       :							str     ,				UpperCAmelCase_       :							Union[str, Any]    )				->     None:

	'''simple docstring'''





	__snake_case     :				Optional[Any] 						=					find_set(_lowercase    ), find_set(_lowercase    )
	if x == y:
		return

	elif x.rank > y.rank:
		__snake_case     :				Any 						=					x
	else:
		__snake_case     :				str 						=					y
		if x.rank == y.rank:
			y.rank += 1
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[Any]    )				->     Node:

	'''simple docstring'''





	if x != x.parent:
		__snake_case     :				Union[str, Any] 						=					find_set(x.parent    )
	return x.parent
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[Any]    )				->     set:

	'''simple docstring'''





	__snake_case     :				Dict 						=					({0, 1, 2}, {3, 4, 5})
	for s in sets:
		if node.data in s:
			return s
	__snake_case     :				Any 						=					F"{node.data} is not in {sets}"
	raise ValueError(_lowercase    )
def     __UpperCAmelCase							(       )				->     None:

	'''simple docstring'''





	__snake_case     :				Dict 						=					[Node(_lowercase    ) for i in range(6    )]
	for v in vertex:
		make_set(_lowercase    )

	union_set(vertex[0]     ,				vertex[1]    )
	union_set(vertex[1]     ,				vertex[2]    )
	union_set(vertex[3]     ,				vertex[4]    )
	union_set(vertex[3]     ,				vertex[5]    )

	for nodea in vertex:
		for nodea in vertex:
			if find_python_set(_lowercase    ).isdisjoint(find_python_set(_lowercase    )    ):
				assert find_set(_lowercase    ) != find_set(_lowercase    )
			else:
				assert find_set(_lowercase    ) == find_set(_lowercase    )


if __name__ == "__main__":
	test_disjoint_set()










'''simple docstring'''




# 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,
)


a  :     Optional[Any]       =       {
    """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:
							a  :     Dict       =       ["""DocumentQuestionAnsweringTool"""]
							a  :     List[str]       =       ["""ImageCaptioningTool"""]
							a  :     Tuple       =       ["""ImageQuestionAnsweringTool"""]
							a  :     Tuple       =       ["""ImageSegmentationTool"""]
							a  :     List[str]       =       ["""SpeechToTextTool"""]
							a  :     Dict       =       ["""TextClassificationTool"""]
							a  :     Union[str, Any]       =       ["""TextQuestionAnsweringTool"""]
							a  :     List[str]       =       ["""TextSummarizationTool"""]
							a  :     Optional[Any]       =       ["""TextToSpeechTool"""]
							a  :     str       =       ["""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

							a  :     Dict       =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

