code: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available
  
  
  SCREAMING_SNAKE_CASE__				:    int         =    {
      """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
  }
  
  try:
     if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     SCREAMING_SNAKE_CASE__				:    List[str]         =    ["""XLMProphetNetTokenizer"""]
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     SCREAMING_SNAKE_CASE__				:    List[Any]         =    [
         """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """XLMProphetNetDecoder""",
         """XLMProphetNetEncoder""",
         """XLMProphetNetForCausalLM""",
         """XLMProphetNetForConditionalGeneration""",
         """XLMProphetNetModel""",
         """XLMProphetNetPreTrainedModel""",
     ]
  
  
  if TYPE_CHECKING:
     from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig
  
     try:
        if not is_sentencepiece_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_xlm_prophetnet import (
            XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLMProphetNetDecoder,
            XLMProphetNetEncoder,
            XLMProphetNetForCausalLM,
            XLMProphetNetForConditionalGeneration,
            XLMProphetNetModel,
            XLMProphetNetPreTrainedModel,
        )
  
  else:
     import sys
  
     SCREAMING_SNAKE_CASE__				:    Dict         =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
style_context: 
  
  
  import os
  
  import requests
  from bsa import BeautifulSoup
  from fake_useragent import UserAgent
  
  SCREAMING_SNAKE_CASE__				:    int         =    {'UserAgent': UserAgent().random}
  SCREAMING_SNAKE_CASE__				:    Tuple         =    'https://www.mywaifulist.moe/random'
  
  
  
  
  def       a__						(		snake_case__				:       str	,      snake_case__				:       str    ):
    _UpperCAmelCase		:       Any       =    requests.get(snake_case__	,      headers=snake_case__    )
    with open(snake_case__	,      """wb"""    ) as file:
      file.write(image.content    )
  
  
  
  
  def       a__						(		):
    _UpperCAmelCase		:       List[Any]       =    BeautifulSoup(requests.get(snake_case__	,      headers=snake_case__    ).text	,      """html.parser"""    )
    _UpperCAmelCase		:       Optional[int]       =    soup.find("""meta"""	,      attrs={"""property""": """og:title"""}    ).attrs["""content"""]
    _UpperCAmelCase		:       int       =    soup.find("""meta"""	,      attrs={"""property""": """og:image"""}    ).attrs["""content"""]
    _UpperCAmelCase		:       Any       =    soup.find("""p"""	,      id="""description"""    ).get_text()
    _UpperCAmelCase,_UpperCAmelCase		:       Dict       =    os.path.splitext(os.path.basename(snake_case__    )    )
    _UpperCAmelCase		:       Tuple       =    title.strip().replace(""" """	,      """_"""    )
    _UpperCAmelCase		:       Optional[Any]       =    f'''{image_title}{image_extension}'''
    save_image(snake_case__	,      snake_case__    )
    return (title, description, image_title)
  
  
  if __name__ == "__main__":
   SCREAMING_SNAKE_CASE__     ,				SCREAMING_SNAKE_CASE__     ,				SCREAMING_SNAKE_CASE__				:    Optional[int]         =    random_anime_character()
   print(F'{title}\n\n{desc}\n\nImage saved : {image_title}')
  
  
  
  
  
  