



'''simple docstring'''




def  __lowerCamelCase    (   _lowercase      ,							_lowercase						) ->     int:
							if a < b:
														return gcd(_lowercase      ,							_lowercase						)
							if a % b == 0:
														return b
							return gcd(_lowercase      ,							a % b						)



def  __lowerCamelCase    (   _lowercase      ,							_lowercase      ,							_lowercase						) ->     int:
							if y == 0:
														return 1
							UpperCAmelCase	:						List[str]					=						power(_lowercase      ,							y // 2      ,							_lowercase						) % mod
							UpperCAmelCase	:						List[Any]					=						(temp * temp) % mod
							if y % 2 == 1:
														UpperCAmelCase	:						List[str]					=						(temp * x) % mod
							return temp



def  __lowerCamelCase    (   _lowercase						) ->     bool:
							UpperCAmelCase	:						Optional[Any]					=						2
							while b < n:
														if gcd(_lowercase      ,							_lowercase						) == 1 and power(_lowercase      ,							n - 1      ,							_lowercase						) != 1:
																					return False
														b += 1
							return True


if __name__ == "__main__":
							a  :     Dict       =       int(input("""Enter number: """).strip())
							if is_carmichael_number(number):
														print(F'''{number} is a Carmichael Number.''')
							else:
														print(F'''{number} is not a Carmichael Number.''')






'''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__)

