






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


lowerCamelCase     :							Tuple    =logging.get_logger(__name__)

lowerCamelCase     :							List[Any]    ={
    '''facebook/data2vec-vision-base-ft''': (
        '''https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json'''
    ),
}





class       __a  (   A__	):
 _lowerCAmelCase	:	Dict				=			'''data2vec-vision'''







 def __init__(		self :       Optional[Any]							,       SCREAMING_SNAKE_CASE :       str=7_68							,       SCREAMING_SNAKE_CASE :       List[Any]=12							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=12							,       SCREAMING_SNAKE_CASE :       Any=30_72							,       SCREAMING_SNAKE_CASE :       List[str]="gelu"							,       SCREAMING_SNAKE_CASE :       Any=0.0							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=0.0							,       SCREAMING_SNAKE_CASE :       Optional[int]=0.0_2							,       SCREAMING_SNAKE_CASE :       Any=1e-1_2							,       SCREAMING_SNAKE_CASE :       str=2_24							,       SCREAMING_SNAKE_CASE :       List[Any]=16							,       SCREAMING_SNAKE_CASE :       Dict=3							,       SCREAMING_SNAKE_CASE :       List[str]=False							,       SCREAMING_SNAKE_CASE :       List[str]=False							,       SCREAMING_SNAKE_CASE :       Optional[Any]=False							,       SCREAMING_SNAKE_CASE :       int=False							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=0.1							,       SCREAMING_SNAKE_CASE :       Tuple=0.1							,       SCREAMING_SNAKE_CASE :       List[Any]=True							,       SCREAMING_SNAKE_CASE :       Dict=[3, 5, 7, 11]							,       SCREAMING_SNAKE_CASE :       List[Any]=[1, 2, 3, 6]							,       SCREAMING_SNAKE_CASE :       List[Any]=True							,       SCREAMING_SNAKE_CASE :       str=0.4							,       SCREAMING_SNAKE_CASE :       Optional[int]=2_56							,       SCREAMING_SNAKE_CASE :       Any=1							,       SCREAMING_SNAKE_CASE :       int=False							,       SCREAMING_SNAKE_CASE :       Optional[Any]=2_55							,       **SCREAMING_SNAKE_CASE :       str							,       ):


      '''simple docstring'''






      super().__init__(**SCREAMING_SNAKE_CASE						)

      UpperCamelCase__      :       List[Any]	    =  hidden_size
      UpperCamelCase__      :       List[str]	    =  num_hidden_layers
      UpperCamelCase__      :       Any	    =  num_attention_heads
      UpperCamelCase__      :       Optional[int]	    =  intermediate_size
      UpperCamelCase__      :       int	    =  hidden_act
      UpperCamelCase__      :       List[str]	    =  hidden_dropout_prob
      UpperCamelCase__      :       Any	    =  attention_probs_dropout_prob
      UpperCamelCase__      :       int	    =  initializer_range
      UpperCamelCase__      :       Any	    =  layer_norm_eps

      UpperCamelCase__      :       List[str]	    =  image_size
      UpperCamelCase__      :       Any	    =  patch_size
      UpperCamelCase__      :       Tuple	    =  num_channels
      UpperCamelCase__      :       Union[str, Any]	    =  use_mask_token
      UpperCamelCase__      :       int	    =  use_absolute_position_embeddings
      UpperCamelCase__      :       List[str]	    =  use_relative_position_bias
      UpperCamelCase__      :       Any	    =  use_shared_relative_position_bias
      UpperCamelCase__      :       List[str]	    =  layer_scale_init_value
      UpperCamelCase__      :       Dict	    =  drop_path_rate
      UpperCamelCase__      :       Any	    =  use_mean_pooling
      # decode head attributes (semantic segmentation)
      UpperCamelCase__      :       List[Any]	    =  out_indices
      UpperCamelCase__      :       List[Any]	    =  pool_scales
      # auxiliary head attributes (semantic segmentation)
      UpperCamelCase__      :       Union[str, Any]	    =  use_auxiliary_head
      UpperCamelCase__      :       Optional[Any]	    =  auxiliary_loss_weight
      UpperCamelCase__      :       Tuple	    =  auxiliary_channels
      UpperCamelCase__      :       Optional[int]	    =  auxiliary_num_convs
      UpperCamelCase__      :       int	    =  auxiliary_concat_input
      UpperCamelCase__      :       Any	    =  semantic_loss_ignore_index







class       __a  (   A__	):
 _lowerCAmelCase	:	List[Any]				=			version.parse('''1.11'''	)







 @property
 def  __lowercase (		self :       List[Any]						):


      '''simple docstring'''






      return OrderedDict(
          [
              ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
          ]						)







 @property
 def  __lowercase (		self :       int						):


      '''simple docstring'''






      return 1e-4







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase      )			->     list:
     UpperCamelCase__      :       Tuple	    =  False
     while is_sorted is False:  # Until all the indices are traversed keep looping
          UpperCamelCase__      :       Tuple	    =  True
          for i in range(0 ,   len(__lowerCAmelCase      ) - 1 ,   2      ):  # iterating over all even indices
               if input_list[i] > input_list[i + 1]:
                    UpperCamelCase__    ,					UpperCamelCase__      :       Dict	    =  input_list[i + 1], input_list[i]
                    # swapping if elements not in order
                    UpperCamelCase__      :       List[str]	    =  False

          for i in range(1 ,   len(__lowerCAmelCase      ) - 1 ,   2      ):  # iterating over all odd indices
               if input_list[i] > input_list[i + 1]:
                    UpperCamelCase__    ,					UpperCamelCase__      :       Optional[int]	    =  input_list[i + 1], input_list[i]
                    # swapping if elements not in order
                    UpperCamelCase__      :       List[Any]	    =  False
     return input_list


if __name__ == "__main__":
 print('''Enter list to be sorted''')
 lowerCamelCase     :							Any    =[int(x) for x in input().split()]
 # inputing elements of the list in one line
 lowerCamelCase     :							Optional[int]    =odd_even_sort(input_list)
 print('''The sorted list is''')
 print(sorted_list)