





'''simple docstring'''







import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowercase__     :  str    					=			logging.get_logger(__name__)

lowercase__     :  List[Any]    					=			{
    """shi-labs/oneformer_ade20k_swin_tiny""": (
        """https://huggingface.co/shi-labs/oneformer_ade20k_swin_tiny/blob/main/config.json"""
    ),
    # See all OneFormer models at https://huggingface.co/models?filter=oneformer
}

class       lowerCamelCase_							(	a__  ):






   '''simple docstring'''

   A :     List[Any]				=	"oneformer"
   A :     str				=	{"hidden_size": "hidden_dim"}


   def __init__(  self     ,						__UpperCamelCase = None     ,						__UpperCamelCase = 2_55     ,						__UpperCamelCase = 1_50     ,						__UpperCamelCase = 0.1     ,						__UpperCamelCase = 2.0     ,						__UpperCamelCase = 5.0     ,						__UpperCamelCase = 5.0     ,						__UpperCamelCase = 0.5     ,						__UpperCamelCase = 0.07     ,						__UpperCamelCase = 1_25_44     ,						__UpperCamelCase = 3.0     ,						__UpperCamelCase = 0.75     ,						__UpperCamelCase = 0.02     ,						__UpperCamelCase = 1.0     ,						__UpperCamelCase = 1e-05     ,						__UpperCamelCase = False     ,						__UpperCamelCase = True     ,						__UpperCamelCase = True     ,						__UpperCamelCase = [4, 8, 16, 32]     ,						__UpperCamelCase = 77     ,						__UpperCamelCase = 2_56     ,						__UpperCamelCase = 77     ,						__UpperCamelCase = 6     ,						__UpperCamelCase = 4_94_08     ,						__UpperCamelCase = 2     ,						__UpperCamelCase = 16     ,						__UpperCamelCase = 2_56     ,						__UpperCamelCase = 2_56     ,						__UpperCamelCase = 2_56     ,						__UpperCamelCase = 10_24     ,						__UpperCamelCase = "GN"     ,						__UpperCamelCase = 6     ,						__UpperCamelCase = 10     ,						__UpperCamelCase = True     ,						__UpperCamelCase = 8     ,						__UpperCamelCase = 0.1     ,						__UpperCamelCase = 20_48     ,						__UpperCamelCase = False     ,						__UpperCamelCase = False     ,						__UpperCamelCase = 2     ,						__UpperCamelCase = 4     ,						**__UpperCamelCase     ,						):







       if backbone_config is None:
           logger.info("`backbone_config` is unset. Initializing the config with the default `Swin` backbone." )
           UpperCamelCase__      =			CONFIG_MAPPING["swin"](
               image_size=2_24     ,						in_channels=3     ,						patch_size=4     ,						embed_dim=96     ,						depths=[2, 2, 6, 2]     ,						num_heads=[3, 6, 12, 24]     ,						window_size=7     ,						drop_path_rate=0.3     ,						use_absolute_embeddings=__A     ,						out_features=["stage1", "stage2", "stage3", "stage4"]     ,						)
       elif isinstance(__A     ,						__A ):
           UpperCamelCase__      =			backbone_config.get("model_type" )
           UpperCamelCase__      =			CONFIG_MAPPING[backbone_model_type]
           UpperCamelCase__      =			config_class.from_dict(__A )

       UpperCamelCase__      =			backbone_config

       UpperCamelCase__      =			ignore_value
       UpperCamelCase__      =			num_queries
       UpperCamelCase__      =			no_object_weight
       UpperCamelCase__      =			class_weight
       UpperCamelCase__      =			mask_weight
       UpperCamelCase__      =			dice_weight
       UpperCamelCase__      =			contrastive_weight
       UpperCamelCase__      =			contrastive_temperature
       UpperCamelCase__      =			train_num_points
       UpperCamelCase__      =			oversample_ratio
       UpperCamelCase__      =			importance_sample_ratio
       UpperCamelCase__      =			init_std
       UpperCamelCase__      =			init_xavier_std
       UpperCamelCase__      =			layer_norm_eps
       UpperCamelCase__      =			is_training
       UpperCamelCase__      =			use_auxiliary_loss
       UpperCamelCase__      =			output_auxiliary_logits
       UpperCamelCase__      =			strides
       UpperCamelCase__      =			task_seq_len
       UpperCamelCase__      =			text_encoder_width
       UpperCamelCase__      =			text_encoder_context_length
       UpperCamelCase__      =			text_encoder_num_layers
       UpperCamelCase__      =			text_encoder_vocab_size
       UpperCamelCase__      =			text_encoder_proj_layers
       UpperCamelCase__      =			text_encoder_n_ctx
       UpperCamelCase__      =			conv_dim
       UpperCamelCase__      =			mask_dim
       UpperCamelCase__      =			hidden_dim
       UpperCamelCase__      =			encoder_feedforward_dim
       UpperCamelCase__      =			norm
       UpperCamelCase__      =			encoder_layers
       UpperCamelCase__      =			decoder_layers
       UpperCamelCase__      =			use_task_norm
       UpperCamelCase__      =			num_attention_heads
       UpperCamelCase__      =			dropout
       UpperCamelCase__      =			dim_feedforward
       UpperCamelCase__      =			pre_norm
       UpperCamelCase__      =			enforce_input_proj
       UpperCamelCase__      =			query_dec_layers
       UpperCamelCase__      =			common_stride
       UpperCamelCase__      =			decoder_layers

       super().__init__(**__A )







   def 	_UpperCamelCase       (  self ):
       UpperCamelCase__      =			copy.deepcopy(self.__dict__ )
       UpperCamelCase__      =			self.backbone_config.to_dict()
       UpperCamelCase__      =			self.__class__.model_type
       return output









'''simple docstring'''







def 						snake_case__ (lowerCAmelCase_	):
    for i, _ in enumerate(lowerCAmelCase_	):
        if (i % 2 == 1) == (nums[i - 1] > nums[i]):
            UpperCamelCase__    ,  UpperCamelCase__      =			nums[i], nums[i - 1]

    return nums


if __name__ == "__main__":
      print('Enter the array elements:')
      lowercase__     :  Optional[int]    					=			list(map(int, input().split()))
      print('The unsorted array is:')
      print(array)
      print('Array after Wiggle sort:')
      print(wiggle_sort(array))




