



import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


__lowerCamelCase     :							Dict  							=				logging.getLogger(__name__)





@dataclass
class  __magic_name__   (							A__						):

		'''simple docstring'''





		lowercase      :       Optional[float]          =field(
		    default=0.0,  metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}						)
		lowercase      :       bool          =field(default=A__,  metadata={'''help''': '''Whether to SortishSamler or not.'''}						)
		lowercase      :       bool          =field(
		    default=A__,  metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}						)
		lowercase      :       bool          =field(default=A__,  metadata={'''help''': '''whether to use adafactor'''}						)
		lowercase      :       Optional[float]          =field(
		    default=A__,  metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}						)
		lowercase      :       Optional[float]          =field(
		    default=A__,  metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}						)
		lowercase      :       Optional[float]          =field(default=A__,  metadata={'''help''': '''Dropout probability. Goes into model.config.'''}						)
		lowercase      :       Optional[float]          =field(
		    default=A__,  metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}						)
		lowercase      :       Optional[str]          =field(
		    default='''linear''',  metadata={'''help''': F"Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()						)}"},  )








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)



