



"""simple docstring"""






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


__UpperCAmelCase   :   Union[str, Any]        =       logging.get_logger(__name__)

__UpperCAmelCase   :   Any        =       {
    'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.json',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}

class 						__lowerCAmelCase				(UpperCamelCase__	):


					'''simple docstring'''


					a__          =  'dpt'







					def __init__(   self     ,							a=7_68     ,							a=12     ,							a=12     ,							a=30_72     ,							a="gelu"     ,							a=0.0     ,							a=0.0     ,							a=0.02     ,							a=1e-1_2     ,							a=3_84     ,							a=16     ,							a=3     ,							a=False     ,							a=True     ,							a=[2, 5, 8, 11]     ,							a="project"     ,							a=[4, 2, 1, 0.5]     ,							a=[96, 1_92, 3_84, 7_68]     ,							a=2_56     ,							a=-1     ,							a=False     ,							a=True     ,							a=0.4     ,							a=2_55     ,							a=0.1     ,							a=[1, 10_24, 24, 24]     ,							a=[0, 1]     ,							a=None     ,							**a     ,							):




										"""simple docstring"""





										super().__init__(**a )

										snake_case_    :Optional[Any]										=    hidden_size
										snake_case_    :Optional[int]										=    is_hybrid

										if self.is_hybrid:
															if backbone_config is None:
																				logger.info("Initializing the config with a `BiT` backbone." )
																				snake_case_    :List[Any]										=    {
																				    "global_padding": "same",
																				    "layer_type": "bottleneck",
																				    "depths": [3, 4, 9],
																				    "out_features": ["stage1", "stage2", "stage3"],
																				    "embedding_dynamic_padding": True,
																				}
																				snake_case_    :int										=    BitConfig(**a )
															elif isinstance(a     ,							a ):
																				logger.info("Initializing the config with a `BiT` backbone." )
																				snake_case_    :int										=    BitConfig(**a )
															elif isinstance(a     ,							a ):
																				snake_case_    :Any										=    backbone_config
															else:
																				raise ValueError(
																				    F'''backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}.''' )

															snake_case_    :List[str]										=    backbone_featmap_shape
															snake_case_    :str										=    neck_ignore_stages

															if readout_type != "project":
																				raise ValueError("Readout type must be 'project' when using `DPT-hybrid` mode." )
										else:
															snake_case_    :Optional[Any]										=    None
															snake_case_    :Optional[int]										=    None
															snake_case_    :List[str]										=    []

										snake_case_    :List[Any]										=    num_hidden_layers
										snake_case_    :Dict										=    num_attention_heads
										snake_case_    :Optional[int]										=    intermediate_size
										snake_case_    :Any										=    hidden_act
										snake_case_    :Dict										=    hidden_dropout_prob
										snake_case_    :Any										=    attention_probs_dropout_prob
										snake_case_    :Tuple										=    initializer_range
										snake_case_    :List[Any]										=    layer_norm_eps
										snake_case_    :Any										=    image_size
										snake_case_    :Optional[int]										=    patch_size
										snake_case_    :Optional[Any]										=    num_channels
										snake_case_    :List[str]										=    qkv_bias
										snake_case_    :int										=    backbone_out_indices
										if readout_type not in ["ignore", "add", "project"]:
															raise ValueError("Readout_type must be one of ['ignore', 'add', 'project']" )
										snake_case_    :int										=    readout_type
										snake_case_    :int										=    reassemble_factors
										snake_case_    :str										=    neck_hidden_sizes
										snake_case_    :Union[str, Any]										=    fusion_hidden_size
										snake_case_    :str										=    head_in_index
										snake_case_    :Any										=    use_batch_norm_in_fusion_residual
										# auxiliary head attributes (semantic segmentation)
										snake_case_    :int										=    use_auxiliary_head
										snake_case_    :Optional[int]										=    auxiliary_loss_weight
										snake_case_    :str										=    semantic_loss_ignore_index
										snake_case_    :Dict										=    semantic_classifier_dropout







					def 		_a			(   self ):




										"""simple docstring"""





										snake_case_    :Tuple										=    copy.deepcopy(self.__dict__ )

										if output["backbone_config"] is not None:
															snake_case_    :Tuple										=    self.backbone_config.to_dict()

										snake_case_    :Any										=    self.__class__.model_type
										return output



'''simple docstring'''
def      UpperCamelCase_				(      A__						):
	if len(A__						) <= 1:
		return lst

	a_      				=						1

	while i < len(A__						):
		if lst[i - 1] <= lst[i]:
			i += 1
		else:
			a_				,  a_      				=						lst[i], lst[i - 1]
			i -= 1
			if i == 0:
				a_      				=						1

	return lst


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