



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


__lowerCamelCase     :							Dict  							=				logging.get_logger(__name__)

__lowerCamelCase     :							Dict  							=				{
    "google/vivit-b-16x2-kinetics400": (
        "https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}





class  __magic_name__   (							A__						):
		lowercase      :       Optional[int]          ='''vivit'''






		def __init__(						self      :     Union[str, Any]				,		UpperCamelCase__      :     Optional[int]=2_24				,		UpperCamelCase__      :     Tuple=32				,		UpperCamelCase__      :     Optional[int]=[2, 16, 16]				,		UpperCamelCase__      :     Dict=3				,		UpperCamelCase__      :     Union[str, Any]=7_68				,		UpperCamelCase__      :     Optional[Any]=12				,		UpperCamelCase__      :     int=12				,		UpperCamelCase__      :     List[Any]=30_72				,		UpperCamelCase__      :     List[Any]="gelu_fast"				,		UpperCamelCase__      :     Optional[Any]=0.0				,		UpperCamelCase__      :     List[Any]=0.0				,		UpperCamelCase__      :     Optional[Any]=0.02				,		UpperCamelCase__      :     Optional[int]=1e-0_6				,		UpperCamelCase__      :     int=True				,		**UpperCamelCase__      :     Union[str, Any]				,		)				->					Any:
								'''simple docstring'''







								UpperCAmelCase         =     hidden_size
								UpperCAmelCase         =     num_hidden_layers
								UpperCAmelCase         =     num_attention_heads
								UpperCAmelCase         =     intermediate_size
								UpperCAmelCase         =     hidden_act
								UpperCAmelCase         =     hidden_dropout_prob
								UpperCAmelCase         =     attention_probs_dropout_prob
								UpperCAmelCase         =     initializer_range
								UpperCAmelCase         =     layer_norm_eps

								UpperCAmelCase         =     image_size
								UpperCAmelCase         =     num_frames
								UpperCAmelCase         =     tubelet_size
								UpperCAmelCase         =     num_channels
								UpperCAmelCase         =     qkv_bias

								super().__init__(**UpperCamelCase__      )








import fire

from utils import calculate_rouge, save_json

def    lowerCamelCase_(lowerCamelCase_    ,   lowerCamelCase_    ,   lowerCamelCase_=None    ,   **lowerCamelCase_    ) ->       Optional[int]:
						UpperCAmelCase         =     [x.strip() for x in open(lowerCamelCase_    ).readlines()]
						UpperCAmelCase         =     [x.strip() for x in open(lowerCamelCase_    ).readlines()][: len(lowerCamelCase_    )]
						UpperCAmelCase         =     calculate_rouge(lowerCamelCase_    ,   lowerCamelCase_    ,   **lowerCamelCase_    )
						if save_path is not None:
												save_json(lowerCamelCase_    ,   lowerCamelCase_    ,   indent=lowerCamelCase_    )
						return metrics  # these print nicely


if __name__ == "__main__":
		fire.Fire(calculate_rouge_path)



