
'''simple docstring'''

import copy

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


UpperCAmelCase__ :			List[str]											=		logging.get_logger(__name__)

UpperCAmelCase__ :			Optional[int]											=		{
    "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  A  (						SCREAMING_SNAKE_CASE__     ):
	snake_case__   :Union[str, Any]   =  'dpt'





	def __init__(       self      :							int   ,				__magic_name__      :							int=768   ,				__magic_name__      :							int=12   ,				__magic_name__      :							Optional[Any]=12   ,				__magic_name__      :							Union[str, Any]=3072   ,				__magic_name__      :							str="gelu"   ,				__magic_name__      :							Optional[int]=0.0   ,				__magic_name__      :							Optional[Any]=0.0   ,				__magic_name__      :							str=0.02   ,				__magic_name__      :							List[str]=1E-12   ,				__magic_name__      :							Union[str, Any]=384   ,				__magic_name__      :							Union[str, Any]=16   ,				__magic_name__      :							Any=3   ,				__magic_name__      :							List[str]=False   ,				__magic_name__      :							int=True   ,				__magic_name__      :							List[Any]=[2, 5, 8, 11]   ,				__magic_name__      :							List[Any]="project"   ,				__magic_name__      :							Tuple=[4, 2, 1, 0.5]   ,				__magic_name__      :							List[str]=[96, 192, 384, 768]   ,				__magic_name__      :							List[str]=256   ,				__magic_name__      :							Any=-1   ,				__magic_name__      :							Dict=False   ,				__magic_name__      :							Any=True   ,				__magic_name__      :							int=0.4   ,				__magic_name__      :							Tuple=255   ,				__magic_name__      :							Union[str, Any]=0.1   ,				__magic_name__      :							Tuple=[1, 1024, 24, 24]   ,				__magic_name__      :							List[Any]=[0, 1]   ,				__magic_name__      :							str=None   ,				**__magic_name__      :							Union[str, Any]   ,				):


				"""simple docstring"""

				super().__init__(**__magic_name__				)

				lowerCAmelCase__										=				hidden_size
				lowerCAmelCase__										=				is_hybrid

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

							lowerCAmelCase__										=				backbone_featmap_shape
							lowerCAmelCase__										=				neck_ignore_stages

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

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







	def 				__SCREAMING_SNAKE_CASE	(       self      :							Optional[int]				):


				"""simple docstring"""

				lowerCAmelCase__										=				copy.deepcopy(self.__dict__				)

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

				lowerCAmelCase__										=				self.__class__.model_type
				return output











'''simple docstring'''

def 						__magic_name__       (      __UpperCAmelCase, __UpperCAmelCase      )						->   int:

					'''simple docstring'''

					return int((input_a, input_a).count(0      ) == 0      )


def 						__magic_name__       (      )						->   None:

					'''simple docstring'''

					assert and_gate(0, 0      ) == 0
					assert and_gate(0, 1      ) == 0
					assert and_gate(1, 0      ) == 0
					assert and_gate(1, 1      ) == 1


if __name__ == "__main__":
							test_and_gate()
							print(and_gate(1, 0))
							print(and_gate(0, 0))
							print(and_gate(0, 1))
							print(and_gate(1, 1))

