


'''simple docstring'''



def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       Dict       ):
					__a      :	List[Any]    =  len(_SCREAMING_SNAKE_CASE       )
					while cur > 1:
										# Find the maximum number in arr
										__a      :	Optional[Any]    =  arr.index(max(arr[0:cur]       )       )
										# Reverse from 0 to mi
										__a      :	List[str]    =  arr[mi::-1] + arr[mi + 1 : len(_SCREAMING_SNAKE_CASE       )]
										# Reverse whole list
										__a      :	Optional[int]    =  arr[cur - 1 :: -1] + arr[cur : len(_SCREAMING_SNAKE_CASE       )]
										cur -= 1
					return arr


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







'''simple docstring'''



from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


__lowercase     :						List[Any]	=     {
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}





class 							__UpperCamelCase    (		lowerCAmelCase_ ):
	A_           =   "ernie_m"
	A_           =   {"dropout": "classifier_dropout", "num_classes": "num_labels"}




	def __init__(       self						,    __a = 25_0002						,    __a = 768						,    __a = 12						,    __a = 12						,    __a = 3072						,    __a = "gelu"						,    __a = 0.1						,    __a = 0.1						,    __a = 514						,    __a = 0.02						,    __a = 1						,    __a = 1E-0_5						,    __a=None						,    __a=False						,    __a=0.0						,    **__a						,    ):

						'''simple docstring'''





						super().__init__(pad_token_id=__a						,    **__a							)
						__a      :	int    =  vocab_size
						__a      :	Dict    =  hidden_size
						__a      :	str    =  num_hidden_layers
						__a      :	Dict    =  num_attention_heads
						__a      :	List[str]    =  intermediate_size
						__a      :	Union[str, Any]    =  hidden_act
						__a      :	List[Any]    =  hidden_dropout_prob
						__a      :	str    =  attention_probs_dropout_prob
						__a      :	Any    =  max_position_embeddings
						__a      :	int    =  initializer_range
						__a      :	Dict    =  layer_norm_eps
						__a      :	int    =  classifier_dropout
						__a      :	Dict    =  is_decoder
						__a      :	int    =  act_dropout



