





"""simple docstring"""






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

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


A			      =	logging.getLogger(__name__)




@dataclass
class 					__lowercase      (      _UpperCamelCase				):







					'''simple docstring'''




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





def lowercase    (  SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE )			->							Dict:


			'''simple docstring'''







			if index == r:
						for j in range(SCREAMING_SNAKE_CASE ):
									print(data[j]       ,    end=' ' )
						print(' ' )
						return
			#  When no more elements are there to put in data[]
			if i >= n:
						return
			# current is included, put next at next location
			SCREAMING_SNAKE_CASE_								=						arr[i]
			combination_util(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    index + 1       ,    SCREAMING_SNAKE_CASE       ,    i + 1 )
			# current is excluded, replace it with
			# next (Note that i+1 is passed, but
			# index is not changed)
			combination_util(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    i + 1 )
			# The main function that prints all combinations
			# of size r in arr[] of size n. This function
			# mainly uses combinationUtil()

def lowercase    (  SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE )			->							Any:


			'''simple docstring'''







			SCREAMING_SNAKE_CASE_								=						[0] * r
			# Print all combination using temporary array 'data[]'
			combination_util(SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    0       ,    SCREAMING_SNAKE_CASE       ,    0 )


if __name__ == "__main__":
				# Driver code to check the function above
				SCREAMING_SNAKE_CASE__     :     Dict		    =       [10, 20, 30, 40, 50]
				print_combination(arr, len(arr), 3)
				# This code is contributed by Ambuj sahu
