'''simple docstring'''





from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
    import torch

if is_vision_available():
    from PIL import Image


SCREAMING_SNAKE_CASE_:	int    =['text', 'image', 'audio']





def       lowerCAmelCase_							(   snake_case_			:					List[str]     )       -> Tuple:


     '''simple docstring'''




     UpperCAmelCase_			       =  []

     for input_type in input_types:
          if input_type == "text":
               inputs.append("Text input"     )
          elif input_type == "image":
               inputs.append(
                   Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"     )     ) / "000000039769.png"     ).resize((5_12, 5_12)     )     )
          elif input_type == "audio":
               inputs.append(torch.ones(30_00     )     )
          elif isinstance(snake_case_   ,       snake_case_     ):
               inputs.append(create_inputs(snake_case_     )     )
          else:
               raise ValueError(f"""Invalid type requested: {input_type}"""     )

     return inputs





def       lowerCAmelCase_							(   snake_case_			:					List     )       -> Tuple:


     '''simple docstring'''




     UpperCAmelCase_			       =  []

     for output in outputs:
          if isinstance(snake_case_   ,       (str, AgentText)     ):
               output_types.append("text"     )
          elif isinstance(snake_case_   ,       (Image.Image, AgentImage)     ):
               output_types.append("image"     )
          elif isinstance(snake_case_   ,       (torch.Tensor, AgentAudio)     ):
               output_types.append("audio"     )
          else:
               raise ValueError(f"""Invalid output: {output}"""     )

     return output_types






@is_tool_test
class 			__A :



    def    _lowercase		(self       :       Optional[Any]					):
         self.assertTrue(hasattr(self.tool  ,     "inputs"					)					)
         self.assertTrue(hasattr(self.tool  ,     "outputs"					)					)

         UpperCAmelCase_			       =  self.tool.inputs
         for _input in inputs:
              if isinstance(_input  ,     __a					):
                   for __input in _input:
                        self.assertTrue(__input in authorized_types					)
              else:
                   self.assertTrue(_input in authorized_types					)

         UpperCAmelCase_			       =  self.tool.outputs
         for _output in outputs:
              self.assertTrue(_output in authorized_types					)



    def    _lowercase		(self       :       List[str]					):
         UpperCAmelCase_			       =  create_inputs(self.tool.inputs					)
         UpperCAmelCase_			       =  self.tool(*__a					)

         # There is a single output
         if len(self.tool.outputs					) == 1:
              UpperCAmelCase_			       =  [outputs]

         self.assertListEqual(output_types(__a					)  ,     self.tool.outputs					)



    def    _lowercase		(self       :       str					):
         self.assertTrue(hasattr(self.tool  ,     "description"					)					)
         self.assertTrue(hasattr(self.tool  ,     "default_checkpoint"					)					)
         self.assertTrue(self.tool.description.startswith("This is a tool that"					)					)



    def    _lowercase		(self       :       Tuple					):
         UpperCAmelCase_			       =  create_inputs(self.tool.inputs					)
         UpperCAmelCase_			       =  self.tool(*__a					)

         if not isinstance(__a  ,     __a					):
              UpperCAmelCase_			       =  [outputs]

         self.assertEqual(len(__a					)  ,     len(self.tool.outputs					)					)

         for output, output_type in zip(__a  ,     self.tool.outputs					):
              UpperCAmelCase_			       =  AGENT_TYPE_MAPPING[output_type]
              self.assertTrue(isinstance(__a  ,     __a					)					)






    def    _lowercase		(self       :       Optional[int]					):
         UpperCAmelCase_			       =  create_inputs(self.tool.inputs					)

         UpperCAmelCase_			       =  []

         for _input, input_type in zip(__a  ,     self.tool.inputs					):
              if isinstance(__a  ,     __a					):
                   _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input					) for _input_type in input_type]					)
              else:
                   _inputs.append(AGENT_TYPE_MAPPING[input_type](_input					)					)

        # Should not raise an error
         UpperCAmelCase_			       =  self.tool(*__a					)

         if not isinstance(__a  ,     __a					):
              UpperCAmelCase_			       =  [outputs]

         self.assertEqual(len(__a					)  ,     len(self.tool.outputs					)					)










def lowercase    (  SCREAMING_SNAKE_CASE )			->							str:


			'''simple docstring'''







			SCREAMING_SNAKE_CASE_								=						len(SCREAMING_SNAKE_CASE )
			while cur > 1:
						# Find the maximum number in arr
						SCREAMING_SNAKE_CASE_								=						arr.index(max(arr[0:cur] ) )
						# Reverse from 0 to mi
						SCREAMING_SNAKE_CASE_								=						arr[mi::-1] + arr[mi + 1 : len(SCREAMING_SNAKE_CASE )]
						# Reverse whole list
						SCREAMING_SNAKE_CASE_								=						arr[cur - 1 :: -1] + arr[cur : len(SCREAMING_SNAKE_CASE )]
						cur -= 1
			return arr


if __name__ == "__main__":
				SCREAMING_SNAKE_CASE__     :     List[str]		    =       input("Enter numbers separated by a comma:\n").strip()
				SCREAMING_SNAKE_CASE__     :     Optional[int]		    =       [int(item) for item in user_input.split(",")]
				print(pancake_sort(unsorted))
