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 				UpperCAmelCase						(    lowercase							):







				"""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(lowercase							,			lowercase							):
												inputs.append(create_inputs(lowercase							)							)
								else:
												raise ValueError(F"Invalid type requested: {input_type}"							)

				return inputs





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							[]

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

				return output_types




@is_tool_test
class    _UpperCamelCase      :


			"""simple docstring"""






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

							'''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      ,   lowerCAmelCase__						):
															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						)     ->					int:

							'''simple docstring'''


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

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

							self.assertListEqual(output_types(lowerCAmelCase__						)      ,   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						)     ->					Union[str, Any]:

							'''simple docstring'''


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

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

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

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





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

							'''simple docstring'''


							__lowercase 			=							create_inputs(self.tool.inputs						)

							__lowercase 			=							[]

							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
							__lowercase 			=							self.tool(*lowerCAmelCase__						)

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

							self.assertEqual(len(lowerCAmelCase__						)      ,   len(self.tool.outputs						)						)
from decimal import Decimal, getcontext
from math import ceil, factorial





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				if not isinstance(lowercase							,			lowercase							):
								raise TypeError('''Undefined for non-integers'''							)
				elif precision < 1:
								raise ValueError('''Undefined for non-natural numbers'''							)

				__lowercase 			=							precision
				__lowercase 			=							ceil(precision / 14							)
				__lowercase 			=							426880 * Decimal(10005							).sqrt()
				__lowercase 			=							1
				__lowercase 			=							13591409
				__lowercase 			=							Decimal(lowercase							)
				for k in range(1							,			lowercase							):
								__lowercase 			=							factorial(6 * k							) // (factorial(3 * k							) * factorial(lowercase							) ** 3)
								linear_term += 545140134
								exponential_term *= -262537412640768000
								partial_sum += Decimal(multinomial_term * linear_term							) / exponential_term
				return str(constant_term / partial_sum							)[:-1]


if __name__ == "__main__":
		__a  :     Optional[Any]       =  5_0
		print(F'''The first {n} digits of pi is: {pi(n)}''')