


'''simple docstring'''






import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


__UpperCAmelCase					       =							logging.getLogger(__name__)




@dataclass
@add_start_docstrings(TrainingArguments.__doc__						)
class 	a__       (							__A						):





		'''simple docstring'''






		lowercase__    :     Optional[Any]					=   field(default=__A       ,       metadata={"help": "Whether to use SortishSampler or not."}						)
		lowercase__    :     Optional[int]					=   field(
		    default=__A       ,       metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}						)
		lowercase__    :     Optional[int]					=   field(
		    default=__A       ,       metadata={
		        "help": (
		            "The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default "
		            "to the `max_length` value of the model configuration."
		        )
		    }       ,       )
		lowercase__    :     Union[str, Any]					=   field(
		    default=__A       ,       metadata={
		        "help": (
		            "The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default "
		            "to the `num_beams` value of the model configuration."
		        )
		    }       ,       )
		lowercase__    :     List[Any]					=   field(
		    default=__A       ,       metadata={
		        "help": "Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."
		    }       ,       )







		def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Dict:
									lowerCAmelCase__      =			super().to_dict()
									for k, v in d.items():
																if isinstance(lowerCamelCase_      ,					lowerCamelCase_     ):
																							lowerCAmelCase__      =			v.to_dict()
									return d



'''simple docstring'''






def       _snake_case     (  A )		->					bool:
							if not isinstance(A				,					A ):
														raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
							if len(A ) == 0:
														raise ValueError('''Input list must be a non empty list''' )
							if len(A ) == 1:
														return True
							lowerCAmelCase__      =			series[1] - series[0]
							for index in range(len(A ) - 1 ):
														if series[index + 1] - series[index] != common_diff:
																					return False
							return True


def       _snake_case     (  A )		->					float:
							if not isinstance(A				,					A ):
														raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
							if len(A ) == 0:
														raise ValueError('''Input list must be a non empty list''' )
							lowerCAmelCase__      =			0
							for val in series:
														answer += val
							return answer / len(A )


if __name__ == "__main__":
		import doctest

		doctest.testmod()