





import functools
import operator

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


lowercase_						=	logging.get_logger(__name__)

lowercase_						=	{
    """asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
    # See all SEW-D models at https://huggingface.co/models?filter=sew-d
}
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):
   _UpperCamelCase					:	Union[str, Any]				      = 'sew-d'


   def __init__(					self    :       Any    ,  a    :       str=32    ,  a    :       Optional[int]=768    ,  a    :       List[str]=12    ,  a    :       Optional[int]=12    ,  a    :       Tuple=3_072    ,  a    :       Optional[Any]=2    ,  a    :       Any=512    ,  a    :       List[str]=256    ,  a    :       int=True    ,  a    :       int=True    ,  a    :       List[Any]=("p2c", "c2p")    ,  a    :       Any="layer_norm"    ,  a    :       str="gelu_python"    ,  a    :       Optional[Any]=0.1    ,  a    :       str=0.1    ,  a    :       Any=0.1    ,  a    :       Tuple=0.0    ,  a    :       List[Any]=0.1    ,  a    :       List[str]=0.02    ,  a    :       Optional[Any]=1E-7    ,  a    :       List[Any]=1E-5    ,  a    :       Optional[int]="group"    ,  a    :       Tuple="gelu"    ,  a    :       List[str]=(64, 128, 128, 128, 128, 256, 256, 256, 256, 512, 512, 512, 512)    ,  a    :       Any=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1)    ,  a    :       str=(10, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)    ,  a    :       List[Any]=False    ,  a    :       Optional[int]=128    ,  a    :       Tuple=16    ,  a    :       Tuple=True    ,  a    :       Optional[Any]=0.05    ,  a    :       List[Any]=10    ,  a    :       Dict=2    ,  a    :       Optional[Any]=0.0    ,  a    :       Optional[Any]=10    ,  a    :       Any=0    ,  a    :       Union[str, Any]="mean"    ,  a    :       List[str]=False    ,  a    :       str=False    ,  a    :       Union[str, Any]=256    ,  a    :       int=0    ,  a    :       Optional[Any]=1    ,  a    :       Tuple=2    ,  **a    :       List[Any]    ,  )->     Optional[Any]:





     """simple docstring"""







     super().__init__(**a    ,  pad_token_id=a    ,  bos_token_id=a    ,  eos_token_id=a )
     lowercase__			    =						hidden_size
     lowercase__			    =						feat_extract_norm
     lowercase__			    =						feat_extract_activation
     lowercase__			    =						list(a )
     lowercase__			    =						list(a )
     lowercase__			    =						list(a )
     lowercase__			    =						conv_bias
     lowercase__			    =						num_conv_pos_embeddings
     lowercase__			    =						num_conv_pos_embedding_groups
     lowercase__			    =						len(self.conv_dim )
     lowercase__			    =						num_hidden_layers
     lowercase__			    =						intermediate_size
     lowercase__			    =						squeeze_factor
     lowercase__			    =						max_position_embeddings
     lowercase__			    =						position_buckets
     lowercase__			    =						share_att_key
     lowercase__			    =						relative_attention
     lowercase__			    =						norm_rel_ebd
     lowercase__			    =						list(a )
     lowercase__			    =						hidden_act
     lowercase__			    =						num_attention_heads
     lowercase__			    =						hidden_dropout
     lowercase__			    =						attention_dropout
     lowercase__			    =						activation_dropout
     lowercase__			    =						feat_proj_dropout
     lowercase__			    =						final_dropout
     lowercase__			    =						layer_norm_eps
     lowercase__			    =						feature_layer_norm_eps
     lowercase__			    =						initializer_range
     lowercase__			    =						vocab_size

     if (
         (len(self.conv_stride ) != self.num_feat_extract_layers)
         or (len(self.conv_kernel ) != self.num_feat_extract_layers)
         or (len(self.conv_dim ) != self.num_feat_extract_layers)
     ):
       raise ValueError(
           'Configuration for convolutional layers is incorrect.'
           'It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,'
           f"""but is `len(config.conv_dim) = {len(self.conv_dim )}`, `len(config.conv_stride)"""
           f"""= {len(self.conv_stride )}`, `len(config.conv_kernel) = {len(self.conv_kernel )}`.""" )

     # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
     lowercase__			    =						apply_spec_augment
     lowercase__			    =						mask_time_prob
     lowercase__			    =						mask_time_length
     lowercase__			    =						mask_time_min_masks
     lowercase__			    =						mask_feature_prob
     lowercase__			    =						mask_feature_length
     lowercase__			    =						mask_feature_min_masks

     # ctc loss
     lowercase__			    =						ctc_loss_reduction
     lowercase__			    =						ctc_zero_infinity

     # sequence classification
     lowercase__			    =						use_weighted_layer_sum
     lowercase__			    =						classifier_proj_size


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[Any] )->     List[Any]:





     """simple docstring"""







     return functools.reduce(operator.mul    ,  self.conv_stride    ,  1 )









def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	)       ->     List[Any]:
  stooge(_SCREAMING_SNAKE_CASE	,		0	,		len(_SCREAMING_SNAKE_CASE	) - 1	)
  return arr




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     int:
  if i >= h:
    return

  # If first element is smaller than the last then swap them
  if arr[i] > arr[h]:
    lowercase__    ,					lowercase__			    =						arr[h], arr[i]

  # If there are more than 2 elements in the array
  if h - i + 1 > 2:
    lowercase__			    =						(int)((h - i + 1) / 3	)

    # Recursively sort first 2/3 elements
    stooge(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		(h - t)	)

    # Recursively sort last 2/3 elements
    stooge(_SCREAMING_SNAKE_CASE	,		i + t	,		(_SCREAMING_SNAKE_CASE)	)

    # Recursively sort first 2/3 elements
    stooge(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		(h - t)	)


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


