



class        snake_case__    :







						"""simple docstring"""




						def __init__(       self ,       __lowercase  ) ->				None:
									"""simple docstring"""




									a__       :						Union[str, Any]							=  len(__lowercase  )
									a__       :						Optional[Any]							=  [0] * len_array

									if len_array > 0:
												a__       :						List[Any]							=  array[0]

									for i in range(1 ,       __lowercase  ):
												a__       :						int							=  self.prefix_sum[i - 1] + array[i]

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase ,       __lowercase  ) ->				int:
									"""simple docstring"""




									if start == 0:
												return self.prefix_sum[end]

									return self.prefix_sum[end] - self.prefix_sum[start - 1]

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				bool:
									"""simple docstring"""




									a__       :						List[Any]							=  {0}
									for sum_item in self.prefix_sum:
												if sum_item - target_sum in sums:
															return True

												sums.add(__lowercase  )

									return False


if __name__ == "__main__":
		import doctest

		doctest.testmod()









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

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


_lowercase		:				str      		=logging.getLogger(__name__)

@dataclass
class        snake_case__    (A__		):







						"""simple docstring"""




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




