


'''simple docstring'''
import copy

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


__snake_case							      =     logging.get_logger(__name__)

__snake_case							      =     {
    '''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	(							A_					):

		"""simple docstring"""

		_a     =				'''dpt'''




		def __init__(		self    ,   UpperCamelCase_=768    ,   UpperCamelCase_=12    ,   UpperCamelCase_=12    ,   UpperCamelCase_=3072    ,   UpperCamelCase_="gelu"    ,   UpperCamelCase_=0.0    ,   UpperCamelCase_=0.0    ,   UpperCamelCase_=0.02    ,   UpperCamelCase_=1e-12    ,   UpperCamelCase_=384    ,   UpperCamelCase_=16    ,   UpperCamelCase_=3    ,   UpperCamelCase_=False    ,   UpperCamelCase_=True    ,   UpperCamelCase_=[2, 5, 8, 11]    ,   UpperCamelCase_="project"    ,   UpperCamelCase_=[4, 2, 1, 0.5]    ,   UpperCamelCase_=[96, 192, 384, 768]    ,   UpperCamelCase_=256    ,   UpperCamelCase_=-1    ,   UpperCamelCase_=False    ,   UpperCamelCase_=True    ,   UpperCamelCase_=0.4    ,   UpperCamelCase_=255    ,   UpperCamelCase_=0.1    ,   UpperCamelCase_=[1, 1024, 24, 24]    ,   UpperCamelCase_=[0, 1]    ,   UpperCamelCase_=None    ,   **UpperCamelCase_    ,   ):

							'''simple docstring'''


							super().__init__(**UpperCamelCase_							)

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

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

												UpperCamelCase__   :Dict												= backbone_featmap_shape
												UpperCamelCase__   :Union[str, Any]												= neck_ignore_stages

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

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




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[Any]												= copy.deepcopy(self.__dict__							)

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

							UpperCamelCase__   :List[Any]												= self.__class__.model_type
							return output



def        _lowerCamelCase(	lowercase__   , lowercase__ = " "	)						->	list:

		'''simple docstring'''







		__lowercase=			[]

		__lowercase=			0
		for index, char in enumerate(lowercase__	):
				if char == separator:
						split_words.append(string[last_index:index]	)
						__lowercase=			index + 1
				elif index + 1 == len(lowercase__	):
						split_words.append(string[last_index : index + 1]	)
		return split_words


if __name__ == "__main__":
	from doctest import testmod

	testmod()






