





'''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


_A:					Tuple							=				["""text""", """image""", """audio"""]







def _lowerCAmelCase     (      _lowerCAmelCase    )->     Dict:
 __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(_lowerCAmelCase       ,    _lowerCAmelCase    ):
   inputs.append(create_inputs(_lowerCAmelCase    )    )
  else:
   raise ValueError(F'Invalid type requested: {input_type}'    )

 return inputs







def _lowerCAmelCase     (      _lowerCAmelCase    )->     List[Any]:
 __UpperCAmelCase					=   []

 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							:



    def 					__lowerCamelCase						(  self					):
     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 					__lowerCamelCase						(  self					):
     __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 					__lowerCamelCase						(  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 					__lowerCamelCase						(  self					):
     __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 					__lowerCamelCase						(  self					):
     __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					)					)












'''simple docstring'''




from __future__ import annotations







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase       ,    )->     tuple:
 if (electron_conc, hole_conc, intrinsic_conc).count(0    ) != 1:
  raise ValueError('You cannot supply more or less than 2 values'    )
 elif electron_conc < 0:
  raise ValueError('Electron concentration cannot be negative in a semiconductor'    )
 elif hole_conc < 0:
  raise ValueError('Hole concentration cannot be negative in a semiconductor'    )
 elif intrinsic_conc < 0:
  raise ValueError(
      'Intrinsic concentration cannot be negative in a semiconductor'    )
 elif electron_conc == 0:
  return (
      "electron_conc",
      intrinsic_conc**2 / hole_conc,
  )
 elif hole_conc == 0:
  return (
      "hole_conc",
      intrinsic_conc**2 / electron_conc,
  )
 elif intrinsic_conc == 0:
  return (
      "intrinsic_conc",
      (electron_conc * hole_conc) ** 0.5,
  )
 else:
  return (-1, -1)


if __name__ == "__main__":
    import doctest

    doctest.testmod()





