






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      	=  ['''text''', '''image''', '''audio''']


def __A    (      __lowerCAmelCase	)->  Optional[int]:





						"""simple docstring"""



						_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((512, 512)	)	)
												elif input_type == "audio":
																		inputs.append(torch.ones(3_000	)	)
												elif isinstance(__lowerCAmelCase ,		__lowerCAmelCase	):
																		inputs.append(create_inputs(__lowerCAmelCase	)	)
												else:
																		raise ValueError(F"""Invalid type requested: {input_type}"""	)

						return inputs


def __A    (      __lowerCAmelCase	)->  Optional[Any]:





						"""simple docstring"""



						_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 __lowerCamelCase :





	"""simple docstring"""






	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







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

							_UpperCAmelCase									=			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    )

							_UpperCAmelCase									=			self.tool.outputs
							for _output in outputs:
													self.assertTrue(_output in authorized_types    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			create_inputs(self.tool.inputs    )
							_UpperCAmelCase									=			self.tool(*UpperCAmelCase    )

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

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

	def        UpperCamelCase    (							self    ):
							"""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        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			create_inputs(self.tool.inputs    )
							_UpperCAmelCase									=			self.tool(*UpperCAmelCase    )

							if not isinstance(UpperCAmelCase       ,    UpperCAmelCase    ):
													_UpperCAmelCase									=			[outputs]

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

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

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			create_inputs(self.tool.inputs    )

							_UpperCAmelCase									=			[]

							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
							_UpperCAmelCase									=			self.tool(*UpperCAmelCase    )

							if not isinstance(UpperCAmelCase       ,    UpperCAmelCase    ):
													_UpperCAmelCase									=			[outputs]

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








from __future__ import annotations


def __A    (      __lowerCAmelCase	)->  list[int]:





						"""simple docstring"""



						_UpperCAmelCase									=			2
						_UpperCAmelCase									=			[]
						while i * i <= n:
												if n % i:
																		i += 1
												else:
																		n //= i
																		factors.append(__lowerCAmelCase	)
						if n > 1:
												factors.append(__lowerCAmelCase	)
						return factors


if __name__ == "__main__":
		import doctest

		doctest.testmod()
