
"""simple docstring"""


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


_lowercase				 =					logging.get_logger(__name__)

_lowercase				 =					{
    """google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}







class 					lowerCAmelCase_					(   SCREAMING_SNAKE_CASE_     ):



						'''simple docstring'''


						_lowerCamelCase:     Optional[int]   =     'pegasus'
						_lowerCamelCase:     str   =     ['past_key_values']
						_lowerCamelCase:     str   =     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}


						def __init__(			self  :   Dict	,A_  :   Tuple=5_0265	,A_  :   List[str]=1024	,A_  :   Optional[Any]=12	,A_  :   List[str]=4096	,A_  :   Optional[Any]=16	,A_  :   Optional[int]=12	,A_  :   Any=4096	,A_  :   Any=16	,A_  :   List[Any]=0.0	,A_  :   List[Any]=0.0	,A_  :   Tuple=True	,A_  :   Any=True	,A_  :   Optional[int]="gelu"	,A_  :   str=1024	,A_  :   List[Any]=0.1	,A_  :   List[Any]=0.0	,A_  :   List[str]=0.0	,A_  :   str=0.02	,A_  :   str=0	,A_  :   Dict=False	,A_  :   Optional[int]=0	,A_  :   str=1	,A_  :   Optional[Any]=1	,**A_  :   Dict	,)  -> Union[str, Any]:
							A     = vocab_size
							A     = max_position_embeddings
							A     = d_model
							A     = encoder_ffn_dim
							A     = encoder_layers
							A     = encoder_attention_heads
							A     = decoder_ffn_dim
							A     = decoder_layers
							A     = decoder_attention_heads
							A     = dropout
							A     = attention_dropout
							A     = activation_dropout
							A     = activation_function
							A     = init_std
							A     = encoder_layerdrop
							A     = decoder_layerdrop
							A     = use_cache
							A     = encoder_layers
							A     = scale_embedding  # scale factor will be sqrt(d_model) if True
							super().__init__(
							    pad_token_id=A_	,eos_token_id=A_	,is_encoder_decoder=A_	,decoder_start_token_id=A_	,forced_eos_token_id=A_	,**A_	,)


						@property
						def     _SCREAMING_SNAKE_CASE   (			self  :   List[Any]   )  -> Any:
							return self.encoder_attention_heads




						@property
						def     _SCREAMING_SNAKE_CASE   (			self  :   str   )  -> Tuple:
							return self.d_model




from datetime import datetime

import requests

def        __a			(   __lowerCAmelCase   )     ->     bytes:
					SCREAMING_SNAKE_CASE							:     int						=				'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
					SCREAMING_SNAKE_CASE							:     Any						=				requests.get(base_url + url   ).json()[0]['urls'][0]['src']
					return requests.get(__lowerCAmelCase   ).content


if __name__ == "__main__":
			_lowerCamelCase    :		List[Any]		      =    input("""Enter Video/IGTV url: """).strip()
			_lowerCamelCase    :		int		      =    f"""{datetime.now():%Y-%m-%d_%H:%M:%S}.mp4"""
			with open(file_name, """wb""") as fp:
						fp.write(download_video(url))
			print(f"""Done. Video saved to disk as {file_name}.""")