def 			A__      (	snake_case_ :		Tuple      ):
	SCREAMING_SNAKE_CASE__:   int=      len(snake_case_      )
	while cur > 1:
		# Find the maximum number in arr
		SCREAMING_SNAKE_CASE__:   Tuple=      arr.index(max(arr[0:cur]      )      )
		# Reverse from 0 to mi
		SCREAMING_SNAKE_CASE__:   int=      arr[mi::-1] + arr[mi + 1 : len(snake_case_      )]
		# Reverse whole list
		SCREAMING_SNAKE_CASE__:   Tuple=      arr[cur - 1 :: -1] + arr[cur : len(snake_case_      )]
		cur -= 1
	return arr


if __name__ == "__main__":
						lowercase_     :   Tuple 				=				input('Enter numbers separated by a comma:\n').strip()
						lowercase_     :   Tuple 				=				[int(item) for item in user_input.split(',')]
						print(pancake_sort(unsorted))


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_     :   List[Any] 				=				logging.get_logger(__name__)

lowercase_     :   List[Any] 				=				{
    'facebook/xlm-roberta-xl': 'https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json',
    'facebook/xlm-roberta-xxl': 'https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}






class 		_lowerCamelCase		(   UpperCamelCase_    ):
    __a  =      "xlm-roberta-xl"
    def __init__(  self , lowerCAmelCase=250880 , lowerCAmelCase=2560 , lowerCAmelCase=36 , lowerCAmelCase=32 , lowerCAmelCase=10240 , lowerCAmelCase="gelu" , lowerCAmelCase=0.1 , lowerCAmelCase=0.1 , lowerCAmelCase=514 , lowerCAmelCase=1 , lowerCAmelCase=0.02 , lowerCAmelCase=1e-05 , lowerCAmelCase=1 , lowerCAmelCase=0 , lowerCAmelCase=2 , lowerCAmelCase="absolute" , lowerCAmelCase=True , lowerCAmelCase=None , **lowerCAmelCase , )       ->					Union[str, Any]:
     super().__init__(pad_token_id=lowerCAmelCase , bos_token_id=lowerCAmelCase , eos_token_id=lowerCAmelCase , **lowerCAmelCase   )
     SCREAMING_SNAKE_CASE__:   List[Any]=      vocab_size
     SCREAMING_SNAKE_CASE__:   Dict=      hidden_size
     SCREAMING_SNAKE_CASE__:   Tuple=      num_hidden_layers
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      num_attention_heads
     SCREAMING_SNAKE_CASE__:   int=      hidden_act
     SCREAMING_SNAKE_CASE__:   Any=      intermediate_size
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      hidden_dropout_prob
     SCREAMING_SNAKE_CASE__:   str=      attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE__:   List[Any]=      max_position_embeddings
     SCREAMING_SNAKE_CASE__:   Dict=      type_vocab_size
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      initializer_range
     SCREAMING_SNAKE_CASE__:   Dict=      layer_norm_eps
     SCREAMING_SNAKE_CASE__:   Dict=      position_embedding_type
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      use_cache
     SCREAMING_SNAKE_CASE__:   str=      classifier_dropout






class 		_lowerCamelCase		(   UpperCamelCase_    ):
    @property
    def 						UpperCamelCase_				(  self   )       ->					Mapping[str, Mapping[int, str]]:
     if self.task == "multiple-choice":
      SCREAMING_SNAKE_CASE__:   Dict=      {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
     else:
      SCREAMING_SNAKE_CASE__:   List[str]=      {0: '''batch''', 1: '''sequence'''}
     return OrderedDict(
         [
             ('''input_ids''', dynamic_axis),
             ('''attention_mask''', dynamic_axis),
         ]   )

