



"""simple docstring"""






import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class  __SCREAMING_SNAKE_CASE			(   __UpperCAmelCase	,     unittest.TestCase     ):


					'''simple docstring'''





					_a         =							BioGptTokenizer
					_a         =							False



					def 	snake_case ( self							:						Union[str, Any]  )->      str:
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								lowerCamelCase__	:	Any				=[
								    '''l''',
								    '''o''',
								    '''w''',
								    '''e''',
								    '''r''',
								    '''s''',
								    '''t''',
								    '''i''',
								    '''d''',
								    '''n''',
								    '''w</w>''',
								    '''r</w>''',
								    '''t</w>''',
								    '''lo''',
								    '''low''',
								    '''er</w>''',
								    '''low</w>''',
								    '''lowest</w>''',
								    '''newer</w>''',
								    '''wider</w>''',
								    '''<unk>''',
								]
								lowerCamelCase__	:	str				=dict(zip(lowerCAmelCase_,						range(len(lowerCAmelCase_  )  )  )  )
								lowerCamelCase__	:	Any				=['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

								lowerCamelCase__	:	List[Any]				=os.path.join(self.tmpdirname,						VOCAB_FILES_NAMES['''vocab_file''']  )
								lowerCamelCase__	:	Any				=os.path.join(self.tmpdirname,						VOCAB_FILES_NAMES['''merges_file''']  )
								with open(self.vocab_file,						'''w'''  ) as fp:
											fp.write(json.dumps(lowerCAmelCase_  )  )
								with open(self.merges_file,						'''w'''  ) as fp:
											fp.write('''\n'''.join(lowerCAmelCase_  )  )



					def 	snake_case ( self							:						Dict,						lowerCamelCase							:						str  )->      Tuple:
								lowerCamelCase__	:	List[Any]				='''lower newer'''
								lowerCamelCase__	:	Union[str, Any]				='''lower newer'''
								return input_text, output_text



					def 	snake_case ( self							:						Optional[int]  )->      str:
								lowerCamelCase__	:	List[Any]				=BioGptTokenizer(self.vocab_file,						self.merges_file  )

								lowerCamelCase__	:	Optional[Any]				='''lower'''
								lowerCamelCase__	:	Tuple				=['''low''', '''er</w>''']
								lowerCamelCase__	:	List[Any]				=tokenizer.tokenize(lowerCAmelCase_  )
								self.assertListEqual(lowerCAmelCase_,						lowerCAmelCase_  )

								lowerCamelCase__	:	Optional[Any]				=tokens + ['''<unk>''']
								lowerCamelCase__	:	Any				=[14, 15, 20]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_  ),						lowerCAmelCase_  )




					@slow
					def 	snake_case ( self							:						Optional[Any]  )->      Tuple:
								lowerCamelCase__	:	Optional[Any]				=BioGptTokenizer.from_pretrained('''microsoft/biogpt'''  )

								lowerCamelCase__	:	Optional[Any]				=tokenizer.encode('''sequence builders''',						add_special_tokens=lowerCAmelCase_  )
								lowerCamelCase__	:	Dict				=tokenizer.encode('''multi-sequence build''',						add_special_tokens=lowerCAmelCase_  )

								lowerCamelCase__	:	List[str]				=tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_  )
								lowerCamelCase__	:	Dict				=tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_,						lowerCAmelCase_  )

								self.assertTrue(encoded_sentence == [2] + text  )
								self.assertTrue(encoded_pair == [2] + text + [2] + text_a  )









"""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()




