






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


lowerCamelCase : List[str]						   =       logging.get_logger(__name__)

lowerCamelCase : Any						   =       {
    '''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     ( __a			):

					'''simple docstring'''

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



					def __init__(  self				:	Optional[int]		,     __a				:	List[str]=50265		,     __a				:	Optional[int]=1024		,     __a				:	Dict=12		,     __a				:	Dict=4096		,     __a				:	Any=16		,     __a				:	Dict=12		,     __a				:	Optional[int]=4096		,     __a				:	List[str]=16		,     __a				:	Optional[Any]=0.0		,     __a				:	List[str]=0.0		,     __a				:	Union[str, Any]=True		,     __a				:	List[Any]=True		,     __a				:	Optional[Any]="gelu"		,     __a				:	Any=1024		,     __a				:	str=0.1		,     __a				:	int=0.0		,     __a				:	Union[str, Any]=0.0		,     __a				:	Dict=0.02		,     __a				:	Dict=0		,     __a				:	Optional[int]=False		,     __a				:	Dict=0		,     __a				:	str=1		,     __a				:	Any=1		,     **__a				:	Union[str, Any]		,     )			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     vocab_size
												__lowercase      :							List[Any]				=     max_position_embeddings
												__lowercase      :							Dict				=     d_model
												__lowercase      :							Any				=     encoder_ffn_dim
												__lowercase      :							Union[str, Any]				=     encoder_layers
												__lowercase      :							Any				=     encoder_attention_heads
												__lowercase      :							Optional[Any]				=     decoder_ffn_dim
												__lowercase      :							str				=     decoder_layers
												__lowercase      :							Optional[int]				=     decoder_attention_heads
												__lowercase      :							Any				=     dropout
												__lowercase      :							Any				=     attention_dropout
												__lowercase      :							int				=     activation_dropout
												__lowercase      :							List[Any]				=     activation_function
												__lowercase      :							List[Any]				=     init_std
												__lowercase      :							Any				=     encoder_layerdrop
												__lowercase      :							Optional[Any]				=     decoder_layerdrop
												__lowercase      :							str				=     use_cache
												__lowercase      :							Dict				=     encoder_layers
												__lowercase      :							int				=     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       lowerCAmelCase				(  self				:	Tuple							)			->  int:


												"""simple docstring"""

												return self.encoder_attention_heads



					@property
					def       lowerCAmelCase				(  self				:	str							)			->  int:


												"""simple docstring"""

												return self.d_model







import fire

from utils import calculate_rouge, save_json
def       snake_case_		(     lowerCAmelCase_       :						Any       ,       lowerCAmelCase_       :						str       ,       lowerCAmelCase_       :						str=None       ,       **lowerCAmelCase_       :						str      ):
							__lowercase      :							Tuple				=     [x.strip() for x in open(lowerCAmelCase_      ).readlines()]
							__lowercase      :							Dict				=     [x.strip() for x in open(lowerCAmelCase_      ).readlines()][: len(lowerCAmelCase_      )]
							__lowercase      :							Tuple				=     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)