code: 
  
  
  
  
  """simple docstring"""
  
  import os
  
  import requests
  from bsa import BeautifulSoup
  from fake_useragent import UserAgent
  
  __A 		=			{"UserAgent": UserAgent().random}
  __A 		=			"https://www.mywaifulist.moe/random"
  
  
  
  def   UpperCamelCase__     (		lowercase__  :     str       ,     lowercase__  :     str   ):
  		snake_case		:						Optional[int]								=				requests.get(lowercase__       ,     headers=lowercase__   )
  		with open(lowercase__       ,     "wb"   ) as file:
  				file.write(image.content   )
  
  
  
  def   UpperCamelCase__     (		):
  		snake_case		:						Optional[int]								=				BeautifulSoup(requests.get(lowercase__       ,     headers=lowercase__   ).text       ,     "html.parser"   )
  		snake_case		:						Dict								=				soup.find("meta"       ,     attrs={"property": "og:title"}   ).attrs["content"]
  		snake_case		:						Union[str, Any]								=				soup.find("meta"       ,     attrs={"property": "og:image"}   ).attrs["content"]
  		snake_case		:						str								=				soup.find("p"       ,     id="description"   ).get_text()
  		snake_case		:						List[Any]								=				os.path.splitext(os.path.basename(lowercase__   )   )
  		snake_case		:						List[str]								=				title.strip().replace(" "       ,     "_"   )
  		snake_case		:						Optional[Any]								=				F'''{image_title}{image_extension}'''
  		save_image(lowercase__       ,     lowercase__   )
  		return (title, description, image_title)
  
  
  if __name__ == "__main__":
  							__A		,       __A		,       __A 		=			random_anime_character()
  							print(f'{title}\n\n{desc}\n\nImage saved : {image_title}')
  
  
  
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
  class 			lowerCamelCase__    (  lowerCamelCase_			):
  			a__ :      Tuple								=     ["""image_processor""", """tokenizer"""]
  			a__ :      List[Any]								=     """EfficientNetImageProcessor"""
  			a__ :      str								=     ("""BertTokenizer""", """BertTokenizerFast""")
  
  
  			def __init__(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					super().__init__(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							)
  
  
  			def __call__(     self				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE="max_length"				, SCREAMING_SNAKE_CASE=64				, SCREAMING_SNAKE_CASE=None				, **SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					if text is None and images is None:
  							raise ValueError("You have to specify either text or images. Both cannot be none."							)
  
  					if text is not None:
  							snake_case		:						Dict								=				self.tokenizer(
  							    SCREAMING_SNAKE_CASE				, padding=SCREAMING_SNAKE_CASE				, max_length=SCREAMING_SNAKE_CASE				, return_tensors=SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  					if images is not None:
  							snake_case		:						Tuple								=				self.image_processor(SCREAMING_SNAKE_CASE				, return_tensors=SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  					if text is not None and images is not None:
  							snake_case		:						Dict								=				image_features.pixel_values
  							return encoding
  					elif text is not None:
  							return encoding
  					else:
  							return BatchEncoding(data=dict(**SCREAMING_SNAKE_CASE							)				, tensor_type=SCREAMING_SNAKE_CASE							)
  
  
  			def 							lowerCamelCase_				(     self				, *SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  
  			def 							lowerCamelCase_				(     self				, *SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					return self.tokenizer.decode(*SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  
  
  			@property
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Optional[Any]								=				self.tokenizer.model_input_names
  					snake_case		:						Any								=				self.image_processor.model_input_names
  					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)
  
  