


"""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


UpperCAmelCase__  							=["text", "image", "audio"]


def lowerCAmelCase_      (				UpperCamelCase__	: List[str] ):






 """simple docstring"""







 __lowercase									=	[]

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

 return inputs


def lowerCAmelCase_      (				UpperCamelCase__	: List ):






 """simple docstring"""







 __lowercase									=	[]

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

 return output_types





@is_tool_test
class    lowerCamelCase__						:
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]							):






       '''simple docstring'''


       self.assertTrue(hasattr(self.tool      ,       """inputs"""							)							)
       self.assertTrue(hasattr(self.tool      ,       """outputs"""							)							)

       __lowercase									=	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							)

       __lowercase									=	self.tool.outputs
       for _output in outputs:
        self.assertTrue(_output in authorized_types							)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]							):






       '''simple docstring'''


       __lowercase									=	create_inputs(self.tool.inputs							)
       __lowercase									=	self.tool(*A_							)

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

       self.assertListEqual(output_types(A_							)      ,       self.tool.outputs							)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]							):






       '''simple docstring'''


       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 SCREAMING_SNAKE_CASE_	(		self	:	Dict							):






       '''simple docstring'''


       __lowercase									=	create_inputs(self.tool.inputs							)
       __lowercase									=	self.tool(*A_							)

       if not isinstance(A_      ,       A_							):
        __lowercase									=	[outputs]

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

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






      def SCREAMING_SNAKE_CASE_	(		self	:	Dict							):






       '''simple docstring'''


       __lowercase									=	create_inputs(self.tool.inputs							)

       __lowercase									=	[]

       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
       __lowercase									=	self.tool(*A_							)

       if not isinstance(A_      ,       A_							):
        __lowercase									=	[outputs]

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




"""simple docstring"""

from __future__ import annotations


def lowerCAmelCase_      (				UpperCamelCase__	: list[float] ):






 """simple docstring"""







 if len(UpperCamelCase__ ) < 2:
  raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
 if any(i <= 0 for i in nums ):
  raise ValueError("""All values must be greater than 0""" )
 __lowercase									=	nums.copy()
 copy_nums.sort()
 return copy_nums[-1] < sum(copy_nums[:-1] )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
