



'''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							:Optional[Any]       = ['text', 'image', 'audio']



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			A_     :						Optional[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((5_12, 5_12)   )   )
						elif input_type == "audio":
									inputs.append(torch.ones(30_00   )   )
						elif isinstance(UpperCamelCase__						,				UpperCamelCase__   ):
									inputs.append(create_inputs(UpperCamelCase__   )   )
						else:
									raise ValueError(f'Invalid type requested: {input_type}'   )

			return inputs



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			A_     :						List[Any]     =					[]

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

				A_     :						Tuple     =					self.tool.inputs
				for _input in inputs:
							if isinstance(_input	,				__lowerCamelCase							):
										for __input in _input:
													self.assertTrue(__input in authorized_types							)
							else:
										self.assertTrue(_input in authorized_types							)

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


	def    _a     (self							):
				A_     :						List[str]     =					create_inputs(self.tool.inputs							)
				A_     :						List[Any]     =					self.tool(*__lowerCamelCase							)

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

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


	def    _a     (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    _a     (self							):
				A_     :						List[str]     =					create_inputs(self.tool.inputs							)
				A_     :						Dict     =					self.tool(*__lowerCamelCase							)

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

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

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


	def    _a     (self							):
				A_     :						Tuple     =					create_inputs(self.tool.inputs							)

				A_     :						Optional[int]     =					[]

				for _input, input_type in zip(__lowerCamelCase	,				self.tool.inputs							):
							if isinstance(__lowerCamelCase	,				__lowerCamelCase							):
										_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
				A_     :						Tuple     =					self.tool(*__lowerCamelCase							)

				if not isinstance(__lowerCamelCase	,				__lowerCamelCase							):
							A_     :						List[str]     =					[outputs]

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











'''simple docstring'''




from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			A_     :						List[Any]     =					prime_factors(lowerCamelCase__   )
			if is_square_free(lowerCamelCase__   ):
						return -1 if len(lowerCamelCase__   ) % 2 else 1
			return 0


if __name__ == "__main__":
						import doctest

						doctest.testmod()