






def 				_a     (   UpperCamelCase_    : Dict      )       ->      Any:
						"""simple docstring"""







						lowerCAmelCase__       					=  len(UpperCamelCase_      )
						while cur > 1:
												# Find the maximum number in arr
												lowerCAmelCase__       					=  arr.index(max(arr[0:cur]      )      )
												# Reverse from 0 to mi
												lowerCAmelCase__       					=  arr[mi::-1] + arr[mi + 1 : len(UpperCamelCase_      )]
												# Reverse whole list
												lowerCAmelCase__       					=  arr[cur - 1 :: -1] + arr[cur : len(UpperCamelCase_      )]
												cur -= 1
						return arr


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










'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case    						=logging.get_logger(__name__)

__snake_case    						={
    """facebook/s2t-wav2vec2-large-en-de""": (
        """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json"""
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}

class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	Union[str, Any]		=     '''speech_to_text_2'''
     lowerCamelCase				:	Any		=     ['''past_key_values''']
     lowerCamelCase				:	Optional[Any]		=     {'''num_attention_heads''': '''decoder_attention_heads''', '''hidden_size''': '''d_model'''}





     def __init__( self       :      Optional[int]    ,      UpperCAmelCase__       :      Optional[Any]=1_0_0_0_0    ,      UpperCAmelCase__       :      int=6    ,      UpperCAmelCase__       :      Optional[Any]=2_0_4_8    ,      UpperCAmelCase__       :      Union[str, Any]=4    ,      UpperCAmelCase__       :      List[Any]=0.0    ,      UpperCAmelCase__       :      str=True    ,      UpperCAmelCase__       :      str="relu"    ,      UpperCAmelCase__       :      Any=2_5_6    ,      UpperCAmelCase__       :      Optional[Any]=0.1    ,      UpperCAmelCase__       :      Any=0.0    ,      UpperCAmelCase__       :      Tuple=0.0    ,      UpperCAmelCase__       :      List[Any]=0.02    ,      UpperCAmelCase__       :      List[Any]=2    ,      UpperCAmelCase__       :      str=True    ,      UpperCAmelCase__       :      List[str]=1    ,      UpperCAmelCase__       :      Any=0    ,      UpperCAmelCase__       :      Dict=2    ,      UpperCAmelCase__       :      int=1_0_2_4    ,      **UpperCAmelCase__       :      Optional[Any]    ,      )				->  Dict:
        lowerCAmelCase     =			vocab_size
        lowerCAmelCase     =			d_model
        lowerCAmelCase     =			decoder_ffn_dim
        lowerCAmelCase     =			decoder_layers
        lowerCAmelCase     =			decoder_attention_heads
        lowerCAmelCase     =			dropout
        lowerCAmelCase     =			attention_dropout
        lowerCAmelCase     =			activation_dropout
        lowerCAmelCase     =			activation_function
        lowerCAmelCase     =			init_std
        lowerCAmelCase     =			decoder_layerdrop
        lowerCAmelCase     =			use_cache
        lowerCAmelCase     =			decoder_layers
        lowerCAmelCase     =			scale_embedding  # scale factor will be sqrt(d_model) if True
        lowerCAmelCase     =			max_target_positions

        super().__init__(
            pad_token_id=UpperCAmelCase__    ,      bos_token_id=UpperCAmelCase__    ,      eos_token_id=UpperCAmelCase__    ,      decoder_start_token_id=UpperCAmelCase__    ,      **UpperCAmelCase__    ,      )





