





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE   						=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   						=		{
    """ZinengTang/tvlt-base""": """https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json""",
}
class SCREAMING_SNAKE_CASE_    (       snake_case_       ):
						__magic_name__:      int			   =							"tvlt"






						def __init__(   self   :   Dict		, _A   :   Tuple=224		, _A   :   Optional[Any]=2048		, _A   :   List[str]=128		, _A   :   Tuple=[16, 16]		, _A   :   List[str]=[16, 16]		, _A   :   Any=3		, _A   :   Tuple=1		, _A   :   Optional[Any]=8		, _A   :   Union[str, Any]=768		, _A   :   Any=12		, _A   :   List[str]=12		, _A   :   Any=3072		, _A   :   Any="gelu"		, _A   :   List[Any]=0.0		, _A   :   Optional[int]=0.0		, _A   :   Tuple=0.0_2		, _A   :   Union[str, Any]=1E-6		, _A   :   Optional[int]=True		, _A   :   Dict=False		, _A   :   List[Any]=16		, _A   :   Dict=512		, _A   :   Union[str, Any]=8		, _A   :   Optional[Any]=2048		, _A   :   Optional[int]=0.7_5		, _A   :   List[str]=0.1_5		, _A   :   Optional[Any]="frame-level"		, _A   :   Tuple=True		, _A   :   Dict=True		, _A   :   Dict="classification"		, **_A   :   List[Any]		, )				->     Dict:







							"""simple docstring"""


							super().__init__(**_A						)

							if audio_mask_type not in ("frame-level", "patch_level"):
								raise ValueError(
								    'audio_mask_type must be one of two acceptable strategies - {\'frame_level\', \'patch-level\') '
								    F"""got {audio_mask_type}"""						)

							snake_case_		:      Tuple           =						image_size
							snake_case_		:      Dict           =						spectrogram_length
							snake_case_		:      int           =						frequency_length
							snake_case_		:      List[Any]           =						image_patch_size
							snake_case_		:      Dict           =						audio_patch_size
							snake_case_		:      List[str]           =						num_image_channels
							snake_case_		:      Optional[Any]           =						num_audio_channels
							snake_case_		:      Optional[int]           =						num_frames

							snake_case_		:      List[str]           =						hidden_size
							snake_case_		:      Optional[Any]           =						num_hidden_layers
							snake_case_		:      Optional[Any]           =						num_attention_heads
							snake_case_		:      Any           =						intermediate_size
							snake_case_		:      List[str]           =						hidden_act
							snake_case_		:      Optional[int]           =						hidden_dropout_prob
							snake_case_		:      int           =						attention_probs_dropout_prob
							snake_case_		:      str           =						initializer_range
							snake_case_		:      str           =						layer_norm_eps
							snake_case_		:      Tuple           =						qkv_bias
							snake_case_		:      str           =						use_mean_pooling

							snake_case_		:      Optional[int]           =						decoder_num_attention_heads
							snake_case_		:      Any           =						decoder_hidden_size
							snake_case_		:      Dict           =						decoder_num_hidden_layers
							snake_case_		:      Dict           =						decoder_intermediate_size
							snake_case_		:      int           =						pixel_mask_ratio
							snake_case_		:      str           =						audio_mask_ratio
							snake_case_		:      Dict           =						audio_mask_type

							snake_case_		:      int           =						task_matching
							snake_case_		:      Dict           =						task_mae
							snake_case_		:      Union[str, Any]           =						loss_type









'''simple docstring'''






import bsa
import requests




def 							_SCREAMING_SNAKE_CASE	(					A	:							bsa.element.ResultSet	)     ->			dict[str, str]:







   """simple docstring"""
   return {
       "name": soup.ha.a.text,
       "genre": soup.find('span'	,		class_='genre'	).text.strip(),
       "rating": soup.strong.text,
       "page_link": F"""https://www.imdb.com{soup.a.get("href"	)}""",
   }




def 							_SCREAMING_SNAKE_CASE	(					A	:							int = 5	)     ->			tuple:







   """simple docstring"""
   __snake_case					:   Optional[int]  				=			int(float(A	)	)
   if num_movies < 1:
      return ()
   __snake_case					:   Union[str, Any]  				=			(
       'https://www.imdb.com/search/title?title_type='
       F"""feature&sort=num_votes,desc&count={num_movies}"""
   )
   __snake_case					:   List[Any]  				=			bsa.BeautifulSoup(requests.get(A	).content	,		'html.parser'	)
   return tuple(
       get_movie_data_from_soup(A	)
       for movie in source.find_all('div'	,		class_='lister-item mode-advanced'	)	)


if __name__ == "__main__":
      import json

      __A     						= int(input('''How many movies would you like to see? '''))
      print(
          ''', '''.join(
              json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
          )
      )