



"""simple docstring"""






import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
		import torch

if is_soundfile_availble():
		import soundfile as sf

if is_vision_available():
		from PIL import Image






def   snake_case__     (	__lowerCamelCase       :					Tuple=""			):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[int]				=tempfile.mkdtemp()
			return os.path.join(__lowerCamelCase							,	str(uuid.uuida()			) + suffix			)

@require_soundfile
@require_torch
class  __SCREAMING_SNAKE_CASE			(   unittest.TestCase     ):


					'''simple docstring'''





					def 	snake_case ( self							:						int  )->      Tuple:
								lowerCamelCase__	:	Optional[int]				=torch.rand(12,						dtype=torch.floataa  ) - 0.5
								lowerCamelCase__	:	str				=AgentAudio(lowerCamelCase  )
								lowerCamelCase__	:	int				=str(agent_type.to_string()  )

								# Ensure that the tensor and the agent_type's tensor are the same
								self.assertTrue(torch.allclose(lowerCamelCase,						agent_type.to_raw(),						atol=1E-4  )  )

								del agent_type

								# Ensure the path remains even after the object deletion
								self.assertTrue(os.path.exists(lowerCamelCase  )  )

								# Ensure that the file contains the same value as the original tensor
								lowerCamelCase__			,     lowerCamelCase__	:	Dict				=sf.read(lowerCamelCase  )
								self.assertTrue(torch.allclose(lowerCamelCase,						torch.tensor(lowerCamelCase  ),						atol=1E-4  )  )




					def 	snake_case ( self							:						Any  )->      List[Any]:
								lowerCamelCase__	:	int				=torch.rand(12,						dtype=torch.floataa  ) - 0.5
								lowerCamelCase__	:	List[Any]				=get_new_path(suffix='''.wav'''  )
								sf.write(lowerCamelCase,						lowerCamelCase,						1_6000  )

								lowerCamelCase__	:	Tuple				=AgentAudio(lowerCamelCase  )

								self.assertTrue(torch.allclose(lowerCamelCase,						agent_type.to_raw(),						atol=1E-4  )  )
								self.assertEqual(agent_type.to_string(),						lowerCamelCase  )





@require_vision
@require_torch
class  __SCREAMING_SNAKE_CASE			(   unittest.TestCase     ):


					'''simple docstring'''





					def 	snake_case ( self							:						Any  )->      List[Any]:
								lowerCamelCase__	:	Tuple				=torch.randint(0,						256,						(64, 64, 3)  )
								lowerCamelCase__	:	Optional[int]				=AgentImage(lowerCamelCase  )
								lowerCamelCase__	:	List[str]				=str(agent_type.to_string()  )

								# Ensure that the tensor and the agent_type's tensor are the same
								self.assertTrue(torch.allclose(lowerCamelCase,						agent_type._tensor,						atol=1E-4  )  )

								self.assertIsInstance(agent_type.to_raw(),						Image.Image  )

								# Ensure the path remains even after the object deletion
								del agent_type
								self.assertTrue(os.path.exists(lowerCamelCase  )  )



					def 	snake_case ( self							:						List[Any]  )->      Tuple:
								lowerCamelCase__	:	Optional[Any]				=Path(get_tests_dir('''fixtures/tests_samples/COCO'''  )  ) / '''000000039769.png'''
								lowerCamelCase__	:	Tuple				=Image.open(lowerCamelCase  )
								lowerCamelCase__	:	List[Any]				=AgentImage(lowerCamelCase  )

								self.assertTrue(path.samefile(agent_type.to_string()  )  )
								self.assertTrue(image == agent_type.to_raw()  )

								# Ensure the path remains even after the object deletion
								del agent_type
								self.assertTrue(os.path.exists(lowerCamelCase  )  )




					def 	snake_case ( self							:						List[str]  )->      Dict:
								lowerCamelCase__	:	Optional[int]				=Path(get_tests_dir('''fixtures/tests_samples/COCO'''  )  ) / '''000000039769.png'''
								lowerCamelCase__	:	int				=Image.open(lowerCamelCase  )
								lowerCamelCase__	:	List[Any]				=AgentImage(lowerCamelCase  )

								self.assertFalse(path.samefile(agent_type.to_string()  )  )
								self.assertTrue(image == agent_type.to_raw()  )

								# Ensure the path remains even after the object deletion
								del agent_type
								self.assertTrue(os.path.exists(lowerCamelCase  )  )





class  __SCREAMING_SNAKE_CASE			(   unittest.TestCase     ):


					'''simple docstring'''





					def 	snake_case ( self							:						str  )->      Optional[Any]:
								lowerCamelCase__	:	Union[str, Any]				='''Hey!'''
								lowerCamelCase__	:	Union[str, Any]				=AgentText(lowerCamelCase  )

								self.assertEqual(lowerCamelCase,						agent_type.to_string()  )
								self.assertEqual(lowerCamelCase,						agent_type.to_raw()  )
								self.assertEqual(lowerCamelCase,						lowerCamelCase  )









"""simple docstring"""






import colorsys

from PIL import Image  # type: ignore






def   snake_case__     (	__lowerCamelCase       :					float							,	__lowerCamelCase       :					float							,	__lowerCamelCase       :					int			):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[Any]				=x
			lowerCamelCase__	:	Any				=y
			for step in range(__lowerCamelCase			):  # noqa: B007
						lowerCamelCase__	:	List[Any]				=a * a - b * b + x
						lowerCamelCase__	:	Optional[int]				=2 * a * b + y
						lowerCamelCase__	:	Union[str, Any]				=a_new

						# divergence happens for all complex number with an absolute value
						# greater than 4
						if a * a + b * b > 4:
									break
			return step / (max_step - 1)






def   snake_case__     (	__lowerCamelCase       :					float			):
			"""simple docstring"""
			if distance == 1:
						return (0, 0, 0)
			else:
						return (255, 255, 255)






def   snake_case__     (	__lowerCamelCase       :					float			):
			"""simple docstring"""
			if distance == 1:
						return (0, 0, 0)
			else:
						return tuple(round(i * 255			) for i in colorsys.hsv_to_rgb(__lowerCamelCase							,	1							,	1			)			)






def   snake_case__     (	__lowerCamelCase       :					int = 800							,	__lowerCamelCase       :					int = 600							,	__lowerCamelCase       :					float = -0.6							,	__lowerCamelCase       :					float = 0							,	__lowerCamelCase       :					float = 3.2							,	__lowerCamelCase       :					int = 50							,	__lowerCamelCase       :					bool = True							,	):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[Any]				=Image.new('''RGB'''							,	(image_width, image_height)			)
			lowerCamelCase__	:	Optional[int]				=img.load()

			# loop through the image-coordinates
			for image_x in range(__lowerCamelCase			):
						for image_y in range(__lowerCamelCase			):
									# determine the figure-coordinates based on the image-coordinates
									lowerCamelCase__	:	Optional[Any]				=figure_width / image_width * image_height
									lowerCamelCase__	:	Dict				=figure_center_x + (image_x / image_width - 0.5) * figure_width
									lowerCamelCase__	:	Optional[int]				=figure_center_y + (image_y / image_height - 0.5) * figure_height

									lowerCamelCase__	:	Any				=get_distance(__lowerCamelCase							,	__lowerCamelCase							,	__lowerCamelCase			)

									# color the corresponding pixel based on the selected coloring-function
									if use_distance_color_coding:
												lowerCamelCase__	:	int				=get_color_coded_rgb(__lowerCamelCase			)
									else:
												lowerCamelCase__	:	Optional[int]				=get_black_and_white_rgb(__lowerCamelCase			)

			return img


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		# colored version, full figure
		_lowercase				:				Optional[Any]   		=		get_image()

		# uncomment for colored version, different section, zoomed in
		# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
		# figure_width = 0.8)

		# uncomment for black and white version, full figure
		# img = get_image(use_distance_color_coding = False)

		# uncomment to save the image
		# img.save("mandelbrot.png")

		img.show()




