



import copy

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


UpperCamelCase__ =						logging.get_logger(__name__)

UpperCamelCase__ =						{
    "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"""





			lowercase__      :  str      =			"""dpt"""





			def __init__(				self	:       Dict			,     lowercase	:       Any=768			,     lowercase	:       str=12			,     lowercase	:       Any=12			,     lowercase	:       Dict=3_072			,     lowercase	:       Dict="gelu"			,     lowercase	:       Any=0.0			,     lowercase	:       Any=0.0			,     lowercase	:       Optional[int]=0.02			,     lowercase	:       int=1E-1_2			,     lowercase	:       List[Any]=384			,     lowercase	:       List[str]=16			,     lowercase	:       Tuple=3			,     lowercase	:       Tuple=False			,     lowercase	:       int=True			,     lowercase	:       Any=[2, 5, 8, 11]			,     lowercase	:       Optional[int]="project"			,     lowercase	:       Optional[Any]=[4, 2, 1, 0.5]			,     lowercase	:       str=[96, 192, 384, 768]			,     lowercase	:       Tuple=256			,     lowercase	:       Optional[Any]=-1			,     lowercase	:       Union[str, Any]=False			,     lowercase	:       List[str]=True			,     lowercase	:       str=0.4			,     lowercase	:       str=255			,     lowercase	:       List[str]=0.1			,     lowercase	:       Dict=[1, 1_024, 24, 24]			,     lowercase	:       List[Any]=[0, 1]			,     lowercase	:       List[str]=None			,     **lowercase	:       Tuple			,     )						->					str:
									"""simple docstring"""







									super().__init__(**lowercase   )

									__lowercase					=				hidden_size
									__lowercase					=				is_hybrid

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

															__lowercase					=				backbone_featmap_shape
															__lowercase					=				neck_ignore_stages

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

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







			def 		snake_case__			(				self	:       str   )						->					Dict:
									"""simple docstring"""







									__lowercase					=				copy.deepcopy(self.__dict__   )

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

									__lowercase					=				self.__class__.model_type
									return output










def  UpperCAmelCase__    (    lowercase__ = 100   ) ->      int:
						__lowercase					=				n * (n + 1) * (2 * n + 1) / 6
						__lowercase					=				(n * (n + 1) / 2) ** 2
						return int(square_of_sum - sum_of_squares   )


if __name__ == "__main__":
			print(F"""{solution() = }""")





