




import copy
from typing import Dict, List, Optional

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


lowercase__				:     str 		=						{
    "facebook/mask2former-swin-small-coco-instance": (
        "https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json"
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

lowercase__				:     int 		=						logging.get_logger(__name__)
class 		UpperCAmelCase   (				UpperCAmelCase__			):







						'''simple docstring'''





						lowerCAmelCase_     		=   '''mask2former'''
						lowerCAmelCase_     		=   ['''swin''']
						lowerCAmelCase_     		=   {'''hidden_size''': '''hidden_dim'''}






						def __init__(						self							:     List[Any]       ,	__lowercase							:     Optional[Dict] = None       ,	__lowercase							:     int = 2_56       ,	__lowercase							:     int = 2_56       ,	__lowercase							:     int = 2_56       ,	__lowercase							:     int = 10_24       ,	__lowercase							:     str = "relu"       ,	__lowercase							:     int = 6       ,	__lowercase							:     int = 10       ,	__lowercase							:     int = 8       ,	__lowercase							:     float = 0.0       ,	__lowercase							:     int = 20_48       ,	__lowercase							:     bool = False       ,	__lowercase							:     bool = False       ,	__lowercase							:     int = 4       ,	__lowercase							:     int = 2_55       ,	__lowercase							:     int = 1_00       ,	__lowercase							:     float = 0.1       ,	__lowercase							:     float = 2.0       ,	__lowercase							:     float = 5.0       ,	__lowercase							:     float = 5.0       ,	__lowercase							:     int = 1_25_44       ,	__lowercase							:     float = 3.0       ,	__lowercase							:     float = 0.75       ,	__lowercase							:     float = 0.02       ,	__lowercase							:     float = 1.0       ,	__lowercase							:     bool = True       ,	__lowercase							:     List[int] = [4, 8, 16, 32]       ,	__lowercase							:     bool = None       ,	**__lowercase							:     List[Any]       ,	):






							"""simple docstring"""






							if backbone_config is None:
								logger.info("`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."						)
								snake_case_		    =     CONFIG_MAPPING["swin"](
								    image_size=2_24       ,	in_channels=3       ,	patch_size=4       ,	embed_dim=96       ,	depths=[2, 2, 18, 2]       ,	num_heads=[3, 6, 12, 24]       ,	window_size=7       ,	drop_path_rate=0.3       ,	use_absolute_embeddings=__lowercase       ,	out_features=["stage1", "stage2", "stage3", "stage4"]       ,	)

							if isinstance(__lowercase       ,	__lowercase						):
								snake_case_		    =     backbone_config.pop("model_type"						)
								snake_case_		    =     CONFIG_MAPPING[backbone_model_type]
								snake_case_		    =     config_class.from_dict(__lowercase						)

							# verify that the backbone is supported
							if backbone_config.model_type not in self.backbones_supported:
								logger.warning_once(
								    f"Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. "
								    f"Supported model types: {','.join(self.backbones_supported						)}"						)

							snake_case_		    =     backbone_config
							snake_case_		    =     feature_size
							snake_case_		    =     mask_feature_size
							snake_case_		    =     hidden_dim
							snake_case_		    =     encoder_feedforward_dim
							snake_case_		    =     activation_function
							snake_case_		    =     encoder_layers
							snake_case_		    =     decoder_layers
							snake_case_		    =     num_attention_heads
							snake_case_		    =     dropout
							snake_case_		    =     dim_feedforward
							snake_case_		    =     pre_norm
							snake_case_		    =     enforce_input_projection
							snake_case_		    =     common_stride
							snake_case_		    =     ignore_value
							snake_case_		    =     num_queries
							snake_case_		    =     no_object_weight
							snake_case_		    =     class_weight
							snake_case_		    =     mask_weight
							snake_case_		    =     dice_weight
							snake_case_		    =     train_num_points
							snake_case_		    =     oversample_ratio
							snake_case_		    =     importance_sample_ratio
							snake_case_		    =     init_std
							snake_case_		    =     init_xavier_std
							snake_case_		    =     use_auxiliary_loss
							snake_case_		    =     feature_strides
							snake_case_		    =     output_auxiliary_logits
							snake_case_		    =     decoder_layers

							super().__init__(**__lowercase						)






						@classmethod
						def        snake_case__						(						cls							:     Optional[int]       ,	__lowercase							:     PretrainedConfig       ,	**__lowercase							:     List[str]						):






							"""simple docstring"""






							return cls(
							    backbone_config=__lowercase       ,	**__lowercase       ,	)






						def        snake_case__						(						self							:     int						):






							"""simple docstring"""






							snake_case_		    =     copy.deepcopy(self.__dict__						)
							snake_case_		    =     self.backbone_config.to_dict()
							snake_case_		    =     self.__class__.model_type
							return output






def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     len(_A							)
	for i in range(_A							):
		for j in range(i + 1     ,	_A							):
			if numbers[j] < numbers[i]:
				snake_case_    ,      snake_case_		    =     numbers[j], numbers[i]
	return numbers


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