



"""simple docstring"""

import copy

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


a_			   =					logging.get_logger(__name__)

a_			   =					{
    '''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    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







						_A		:							Tuple							       =		"""dpt"""







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

											snake_case_					:		Any 					=					hidden_size
											snake_case_					:		List[Any] 					=					is_hybrid

											if self.is_hybrid:
																if backbone_config is None:
																					logger.info("""Initializing the config with a `BiT` backbone."""       )
																					snake_case_					:		Tuple 					=					{
																					    """global_padding""": """same""",
																					    """layer_type""": """bottleneck""",
																					    """depths""": [3, 4, 9],
																					    """out_features""": ["""stage1""", """stage2""", """stage3"""],
																					    """embedding_dynamic_padding""": True,
																					}
																					snake_case_					:		Any 					=					BitConfig(**lowercase__       )
																elif isinstance(lowercase__   ,		lowercase__       ):
																					logger.info("""Initializing the config with a `BiT` backbone."""       )
																					snake_case_					:		List[Any] 					=					BitConfig(**lowercase__       )
																elif isinstance(lowercase__   ,		lowercase__       ):
																					snake_case_					:		str 					=					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_					:		Any 					=					neck_ignore_stages

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

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Any 					=					copy.deepcopy(self.__dict__       )

											if output["backbone_config"] is not None:
																snake_case_					:		Union[str, Any] 					=					self.backbone_config.to_dict()

											snake_case_					:		Tuple 					=					self.__class__.model_type
											return output









"""simple docstring"""

def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  list			):



					"""simple docstring"""





					snake_case_					:		Optional[int] 					=					len(SCREAMING_SNAKE_CASE__			)
					for i in range(1				,    SCREAMING_SNAKE_CASE__			):
										snake_case_					:		Tuple 					=					collection[i]
										snake_case_					:		Tuple 					=					0
										snake_case_					:		str 					=					i - 1

										while low <= high:
															snake_case_					:		Optional[int] 					=					(low + high) // 2
															if val < collection[mid]:
																				snake_case_					:		List[str] 					=					mid - 1
															else:
																				snake_case_					:		str 					=					mid + 1
										for j in range(SCREAMING_SNAKE_CASE__				,    SCREAMING_SNAKE_CASE__				,    -1			):
															snake_case_					:		List[str] 					=					collection[j - 1]
										snake_case_					:		Any 					=					val
					return collection


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




