




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__       :      List[Any]  =   ['''text''', '''image''', '''audio''']

def      A      (      _SCREAMING_SNAKE_CASE    )	-> Tuple:
       lowerCamelCase   :      str			 =					[]

       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((512, 512)    )    )
              elif input_type == "audio":
                     inputs.append(torch.ones(3000    )    )
              elif isinstance(lowerCAmelCase_ ,lowerCAmelCase_    ):
                     inputs.append(create_inputs(lowerCAmelCase_    )    )
              else:
                     raise ValueError(f'''Invalid type requested: {input_type}'''    )

       return inputs

def      A      (      _SCREAMING_SNAKE_CASE    )	-> str:
       lowerCamelCase   :      Optional[int]			 =					[]

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

       return output_types




@is_tool_test
class 		UpperCamelCase__	:

    '''simple docstring'''



    def     _lowercase     (    self     )     ->      List[str]:
           self.assertTrue(hasattr(self.tool     ,  "inputs"     )     )
           self.assertTrue(hasattr(self.tool     ,  "outputs"     )     )

           lowerCamelCase   :      Tuple			 =					self.tool.inputs
           for _input in inputs:
                  if isinstance(_input     ,  UpperCAmelCase__     ):
                         for __input in _input:
                                self.assertTrue(__input in authorized_types     )
                  else:
                         self.assertTrue(_input in authorized_types     )

           lowerCamelCase   :      List[str]			 =					self.tool.outputs
           for _output in outputs:
                  self.assertTrue(_output in authorized_types     )







    def     _lowercase     (    self     )     ->      List[Any]:
           lowerCamelCase   :      Dict			 =					create_inputs(self.tool.inputs     )
           lowerCamelCase   :      Tuple			 =					self.tool(*UpperCAmelCase__     )

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

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







    def     _lowercase     (    self     )     ->      int:
           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     )     ->      Optional[int]:
           lowerCamelCase   :      Union[str, Any]			 =					create_inputs(self.tool.inputs     )
           lowerCamelCase   :      Optional[Any]			 =					self.tool(*UpperCAmelCase__     )

           if not isinstance(UpperCAmelCase__     ,  UpperCAmelCase__     ):
                  lowerCamelCase   :      str			 =					[outputs]

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

           for output, output_type in zip(UpperCAmelCase__     ,  self.tool.outputs     ):
                  lowerCamelCase   :      Optional[int]			 =					AGENT_TYPE_MAPPING[output_type]
                  self.assertTrue(isinstance(UpperCAmelCase__     ,  UpperCAmelCase__     )     )







    def     _lowercase     (    self     )     ->      Tuple:
           lowerCamelCase   :      Any			 =					create_inputs(self.tool.inputs     )

           lowerCamelCase   :      int			 =					[]

           for _input, input_type in zip(UpperCAmelCase__     ,  self.tool.inputs     ):
                  if isinstance(UpperCAmelCase__     ,  UpperCAmelCase__     ):
                         _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
           lowerCamelCase   :      Tuple			 =					self.tool(*UpperCAmelCase__     )

           if not isinstance(UpperCAmelCase__     ,  UpperCAmelCase__     ):
                  lowerCamelCase   :      Optional[Any]			 =					[outputs]

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










"""simple docstring"""







from __future__ import annotations




def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_ = None  ,						lowerCAmelCase_ = None   ):




					'''simple docstring'''


					if start is None:
										__SCREAMING_SNAKE_CASE						   =				0

					if end is None:
										__SCREAMING_SNAKE_CASE						   =				len(lowerCAmelCase_   ) - 1

					if start >= end:
										return

					__SCREAMING_SNAKE_CASE						   =				(start + end) // 2

					slowsort(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_   )
					slowsort(lowerCAmelCase_  ,						mid + 1  ,						lowerCAmelCase_   )

					if sequence[end] < sequence[mid]:
										__SCREAMING_SNAKE_CASE   ,  __SCREAMING_SNAKE_CASE						   =				sequence[mid], sequence[end]

					slowsort(lowerCAmelCase_  ,						lowerCAmelCase_  ,						end - 1   )


if __name__ == "__main__":
		from doctest import testmod

		testmod()
