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







def 						A__  (					__A	):







    '''simple docstring'''
    _lowerCamelCase     :		Any 						=						[]

    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(3_000	)	)
        elif isinstance(__A   , __A	):
            inputs.append(create_inputs(__A	)	)
        else:
            raise ValueError(F"""Invalid type requested: {input_type}"""	)

    return inputs







def 						A__  (					__A	):







    '''simple docstring'''
    _lowerCamelCase     :		List[str] 						=						[]

    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 	__snake_case	:





      '''simple docstring'''






      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any])				->Any:


          """simple docstring"""


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

          _lowerCamelCase     :		Dict 						=						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     :		Union[str, Any] 						=						self.tool.outputs
          for _output in outputs:
              self.assertTrue(_output in authorized_types)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				str)				->Dict:


          """simple docstring"""


          _lowerCamelCase     :		Tuple 						=						create_inputs(self.tool.inputs)
          _lowerCamelCase     :		Optional[int] 						=						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 	_SCREAMING_SNAKE_CASE    (					self     :				int)				->Union[str, 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     :				List[str])				->List[str]:


          """simple docstring"""


          _lowerCamelCase     :		str 						=						create_inputs(self.tool.inputs)
          _lowerCamelCase     :		Union[str, Any] 						=						self.tool(*_UpperCamelCase)

          if not isinstance(_UpperCamelCase    ,  _UpperCamelCase):
              _lowerCamelCase     :		Union[str, Any] 						=						[outputs]

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

          for output, output_type in zip(_UpperCamelCase    ,  self.tool.outputs):
              _lowerCamelCase     :		str 						=						AGENT_TYPE_MAPPING[output_type]
              self.assertTrue(isinstance(_UpperCamelCase    ,  _UpperCamelCase))




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Dict)				->List[str]:


          """simple docstring"""


          _lowerCamelCase     :		int 						=						create_inputs(self.tool.inputs)

          _lowerCamelCase     :		str 						=						[]

          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     :		int 						=						[outputs]

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





def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _enforce_args(__A   , __A	)
    if n == 0:
        return 0
    _lowerCamelCase     :		Tuple 						=						float("""-inf"""	)
    for i in range(1   , n + 1	):
        _lowerCamelCase     :		Any 						=						max(
            __A   , prices[i - 1] + naive_cut_rod_recursive(n - i   , __A	)	)

    return max_revue







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _enforce_args(__A   , __A	)
    _lowerCamelCase     :		Optional[Any] 						=						[float("""-inf"""	) for _ in range(n + 1	)]
    return _top_down_cut_rod_recursive(__A   , __A   , __A	)







def 						A__  (					__A   , __A   , __A	):







    '''simple docstring'''
    if max_rev[n] >= 0:
        return max_rev[n]
    elif n == 0:
        return 0
    else:
        _lowerCamelCase     :		int 						=						float("""-inf"""	)
        for i in range(1   , n + 1	):
            _lowerCamelCase     :		Optional[Any] 						=						max(
                __A   , prices[i - 1] + _top_down_cut_rod_recursive(n - i   , __A   , __A	)   , )

        _lowerCamelCase     :		Optional[Any] 						=						max_revenue

    return max_rev[n]







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _enforce_args(__A   , __A	)

    # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
    # length 0.
    _lowerCamelCase     :		List[Any] 						=						[float("""-inf"""	) for _ in range(n + 1	)]
    _lowerCamelCase     :		Any 						=						0

    for i in range(1   , n + 1	):
        _lowerCamelCase     :		Any 						=						max_rev[i]
        for j in range(1   , i + 1	):
            _lowerCamelCase     :		List[Any] 						=						max(__A   , prices[j - 1] + max_rev[i - j]	)

        _lowerCamelCase     :		int 						=						max_revenue_i

    return max_rev[n]







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    if n < 0:
        _lowerCamelCase     :		Any 						=						F"""n must be greater than or equal to 0. Got n = {n}"""
        raise ValueError(__A	)

    if n > len(__A	):
        _lowerCamelCase     :		List[Any] 						=						(
            """Each integral piece of rod must have a corresponding price. """
            F"""Got n = {n} but length of prices = {len(__A	)}"""
        )
        raise ValueError(__A	)







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		str 						=						[6, 10, 12, 15, 20, 23]
    _lowerCamelCase     :		List[str] 						=						len(__A	)

    # the best revenue comes from cutting the rod into 6 pieces, each
    # of length 1 resulting in a revenue of 6 * 6 = 36.
    _lowerCamelCase     :		Tuple 						=						36

    _lowerCamelCase     :		Any 						=						top_down_cut_rod(__A   , __A	)
    _lowerCamelCase     :		Dict 						=						bottom_up_cut_rod(__A   , __A	)
    _lowerCamelCase     :		List[str] 						=						naive_cut_rod_recursive(__A   , __A	)

    assert expected_max_revenue == max_rev_top_down
    assert max_rev_top_down == max_rev_bottom_up
    assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
    main()




