





'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

from packaging import version

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


__SCREAMING_SNAKE_CASE     :Optional[Any]       =				logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE     :Dict       =				{
    '''google/mobilenet_v2_1.4_224''': '''https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json''',
    '''google/mobilenet_v2_1.0_224''': '''https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json''',
    '''google/mobilenet_v2_0.75_160''': '''https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json''',
    '''google/mobilenet_v2_0.35_96''': '''https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json''',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}







class   A_	(  lowerCAmelCase_			):
 _lowerCamelCase  : List[Any]           =							"""mobilenet_v2"""




 def __init__(					self       :    str	,			snake_case_       :    List[str]=3	,			snake_case_       :    Any=2_2_4	,			snake_case_       :    Union[str, Any]=1.0	,			snake_case_       :    int=8	,			snake_case_       :    List[str]=8	,			snake_case_       :    Dict=6	,			snake_case_       :    Union[str, Any]=3_2	,			snake_case_       :    Optional[int]=True	,			snake_case_       :    Optional[Any]=True	,			snake_case_       :    Optional[Any]="relu6"	,			snake_case_       :    int=True	,			snake_case_       :    Any=0.8	,			snake_case_       :    List[str]=0.0_2	,			snake_case_       :    Optional[int]=0.0_0_1	,			snake_case_       :    Dict=2_5_5	,			**snake_case_       :    Dict	,			):
      super().__init__(**snake_case_    )

      if depth_multiplier <= 0:
           raise ValueError("depth_multiplier must be greater than zero."    )

      _UpperCAmelCase     							=   num_channels
      _UpperCAmelCase     							=   image_size
      _UpperCAmelCase     							=   depth_multiplier
      _UpperCAmelCase     							=   depth_divisible_by
      _UpperCAmelCase     							=   min_depth
      _UpperCAmelCase     							=   expand_ratio
      _UpperCAmelCase     							=   output_stride
      _UpperCAmelCase     							=   first_layer_is_expansion
      _UpperCAmelCase     							=   finegrained_output
      _UpperCAmelCase     							=   hidden_act
      _UpperCAmelCase     							=   tf_padding
      _UpperCAmelCase     							=   classifier_dropout_prob
      _UpperCAmelCase     							=   initializer_range
      _UpperCAmelCase     							=   layer_norm_eps
      _UpperCAmelCase     							=   semantic_loss_ignore_index







class   A_	(  lowerCAmelCase_			):
 _lowerCamelCase  : Optional[int]           =							version.parse("""1.11"""			)




 @property
 def      lowercase	(					self       :    Optional[int]    ):
      return OrderedDict([("pixel_values", {0: "batch"})]    )




 @property
 def      lowercase	(					self       :    Union[str, Any]    ):
      if self.task == "image-classification":
           return OrderedDict([("logits", {0: "batch"})]    )
      else:
           return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]    )




 @property
 def      lowercase	(					self       :    List[Any]    ):
      return 1e-4











def      _A       (		SCREAMING_SNAKE_CASE     :   Optional[Any]						):





  """simple docstring"""



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


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






