






'''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


__lowerCamelCase	:		str										=   ["""text""", """image""", """audio"""]







def 			A__							(      _a  :					List[str]	):





 '''simple docstring'''







 snake_case__  :    int							       =[]

 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(_a		,  _a	):
   inputs.append(create_inputs(_a	)	)
  else:
   raise ValueError(f"Invalid type requested: {input_type}"	)

 return inputs







def 			A__							(      _a  :					List	):





 '''simple docstring'''







 snake_case__  :    int							       =[]

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

 return output_types







@is_tool_test
class  _lowercase   :
      def 						lowercase__					(     self   ):
       self.assertTrue(hasattr(self.tool				,			"""inputs"""   )   )
       self.assertTrue(hasattr(self.tool				,			"""outputs"""   )   )

       snake_case__  :    Dict							       =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   )

       snake_case__  :    Dict							       =self.tool.outputs
       for _output in outputs:
        self.assertTrue(_output in authorized_types   )
      def 						lowercase__					(     self   ):
       snake_case__  :    List[Any]							       =create_inputs(self.tool.inputs   )
       snake_case__  :    List[str]							       =self.tool(*a   )

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

       self.assertListEqual(output_types(a   )				,			self.tool.outputs   )
      def 						lowercase__					(     self   ):
       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   ):
       snake_case__  :    Optional[Any]							       =create_inputs(self.tool.inputs   )
       snake_case__  :    int							       =self.tool(*a   )

       if not isinstance(a				,			a   ):
        snake_case__  :    List[Any]							       =[outputs]

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

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



      def 						lowercase__					(     self   ):
       snake_case__  :    List[Any]							       =create_inputs(self.tool.inputs   )

       snake_case__  :    Optional[int]							       =[]

       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
       snake_case__  :    Tuple							       =self.tool(*a   )

       if not isinstance(a				,			a   ):
        snake_case__  :    Optional[Any]							       =[outputs]

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













__lowerCamelCase	:		dict[str, float]										=   {
    "km/h": 1.0,
    "m/s": 3.6,
    "mph": 1.60_93_44,
    "knot": 1.8_52,
}

__lowerCamelCase	:		dict[str, float]										=   {
    "km/h": 1.0,
    "m/s": 0.2_77_77_77_78,
    "mph": 0.6_21_37_11_92,
    "knot": 0.5_39_95_68_03,
}







def 			A__							(      _a  :					float		,  _a  :					str		,  _a  :					str	):





 '''simple docstring'''







 if unit_to not in speed_chart or unit_from not in speed_chart_inverse:
  snake_case__  :    Tuple							       =(
      f"Incorrect 'from_type' or 'to_type' value: {unit_from!r}, {unit_to!r}\n"
      f"Valid values are: {', '.join(_a	)}"
  )
  raise ValueError(_a	)
 return round(speed * speed_chart[unit_from] * speed_chart_inverse[unit_to]		,  3	)


if __name__ == "__main__":
       import doctest

       doctest.testmod()





