




def 					__SCREAMING_SNAKE_CASE   (  lowercase_      )       ->	Union[str, Any]:

    """simple docstring"""


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








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


a_   		=     logging.get_logger(__name__)

a_   		=     {
    "speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}

class  _lowerCamelCase						(			_SCREAMING_SNAKE_CASE   ):

      """simple docstring"""

      lowerCAmelCase__			: int    =					"mctct"







      def __init__(     self					: List[Any] ,       snake_case					: Optional[Any]=8065 ,       snake_case					: Optional[int]=1536 ,       snake_case					: Any=36 ,       snake_case					: List[str]=6144 ,       snake_case					: Dict=4 ,       snake_case					: str=384 ,       snake_case					: List[str]=920 ,       snake_case					: Dict=1E-5 ,       snake_case					: Union[str, Any]=0.3 ,       snake_case					: Optional[Any]="relu" ,       snake_case					: str=0.02 ,       snake_case					: Optional[int]=0.3 ,       snake_case					: int=0.3 ,       snake_case					: Any=1 ,       snake_case					: int=0 ,       snake_case					: Union[str, Any]=2 ,       snake_case					: List[Any]=1 ,       snake_case					: Dict=0.3 ,       snake_case					: int=1 ,       snake_case					: Optional[int]=(7,) ,       snake_case					: List[Any]=(3,) ,       snake_case					: Optional[int]=80 ,       snake_case					: List[str]=1 ,       snake_case					: int=None ,       snake_case					: List[str]="sum" ,       snake_case					: Tuple=False ,       **snake_case					: List[str] ,       ):
          super().__init__(**snake_case ,       pad_token_id=snake_case ,       bos_token_id=snake_case ,       eos_token_id=snake_case				)
          __UpperCamelCase  		=						vocab_size
          __UpperCamelCase  		=						hidden_size
          __UpperCamelCase  		=						num_hidden_layers
          __UpperCamelCase  		=						intermediate_size
          __UpperCamelCase  		=						num_attention_heads
          __UpperCamelCase  		=						attention_head_dim
          __UpperCamelCase  		=						max_position_embeddings
          __UpperCamelCase  		=						layer_norm_eps
          __UpperCamelCase  		=						layerdrop
          __UpperCamelCase  		=						hidden_act
          __UpperCamelCase  		=						initializer_range
          __UpperCamelCase  		=						hidden_dropout_prob
          __UpperCamelCase  		=						attention_probs_dropout_prob
          __UpperCamelCase  		=						pad_token_id
          __UpperCamelCase  		=						bos_token_id
          __UpperCamelCase  		=						eos_token_id
          __UpperCamelCase  		=						conv_glu_dim
          __UpperCamelCase  		=						conv_dropout
          __UpperCamelCase  		=						num_conv_layers
          __UpperCamelCase  		=						input_feat_per_channel
          __UpperCamelCase  		=						input_channels
          __UpperCamelCase  		=						conv_channels
          __UpperCamelCase  		=						ctc_loss_reduction
          __UpperCamelCase  		=						ctc_zero_infinity

          # prevents config testing fail with exporting to json
          __UpperCamelCase  		=						list(snake_case				)
          __UpperCamelCase  		=						list(snake_case				)

          if len(self.conv_kernel				) != self.num_conv_layers:
              raise ValueError(
                  '''Configuration for convolutional module is incorrect. '''
                  '''It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '''
                  F"but is `len(config.conv_kernel) = {len(self.conv_kernel				)}`, "
                  F"`config.num_conv_layers = {self.num_conv_layers}`."				)






