




"""simple docstring"""

import copy

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


_lowerCamelCase  :			str        =       logging.get_logger(__name__)

_lowerCamelCase  :			List[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        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Tuple         =   """dpt"""







				def __init__(							self   :					Optional[int]      ,     _lowerCamelCase   :					Optional[int]=7_68      ,     _lowerCamelCase   :					Tuple=12      ,     _lowerCamelCase   :					Union[str, Any]=12      ,     _lowerCamelCase   :					Any=30_72      ,     _lowerCamelCase   :					int="gelu"      ,     _lowerCamelCase   :					Dict=0.0      ,     _lowerCamelCase   :					Tuple=0.0      ,     _lowerCamelCase   :					int=0.02      ,     _lowerCamelCase   :					Dict=1E-12      ,     _lowerCamelCase   :					Any=3_84      ,     _lowerCamelCase   :					Optional[Any]=16      ,     _lowerCamelCase   :					Optional[int]=3      ,     _lowerCamelCase   :					List[Any]=False      ,     _lowerCamelCase   :					Optional[Any]=True      ,     _lowerCamelCase   :					str=[2, 5, 8, 11]      ,     _lowerCamelCase   :					List[Any]="project"      ,     _lowerCamelCase   :					Dict=[4, 2, 1, 0.5]      ,     _lowerCamelCase   :					Any=[96, 1_92, 3_84, 7_68]      ,     _lowerCamelCase   :					int=2_56      ,     _lowerCamelCase   :					Any=-1      ,     _lowerCamelCase   :					Optional[Any]=False      ,     _lowerCamelCase   :					List[Any]=True      ,     _lowerCamelCase   :					List[Any]=0.4      ,     _lowerCamelCase   :					Union[str, Any]=2_55      ,     _lowerCamelCase   :					Any=0.1      ,     _lowerCamelCase   :					str=[1, 10_24, 24, 24]      ,     _lowerCamelCase   :					List[str]=[0, 1]      ,     _lowerCamelCase   :					str=None      ,     **_lowerCamelCase   :					Optional[Any]      ,     ):



					"""simple docstring"""

					super().__init__(**_lowerCamelCase       )

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

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

						A_  :				List[str]	   =		backbone_featmap_shape
						A_  :				Dict	   =		neck_ignore_stages

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

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







				def 					a_  (							self   :					Any       ):



					"""simple docstring"""

					A_  :				Dict	   =		copy.deepcopy(self.__dict__       )

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

					A_  :				Dict	   =		self.__class__.model_type
					return output











"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCamelCase  :			Optional[Any]        =       logging.get_logger(__name__)

_lowerCamelCase  :			Any        =       {
    'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
    'studio-ousia/luke-large': 'https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json',
}

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Any         =   """luke"""







				def __init__(							self   :					List[str]      ,     _lowerCamelCase   :					Union[str, Any]=5_02_67      ,     _lowerCamelCase   :					Tuple=50_00_00      ,     _lowerCamelCase   :					int=7_68      ,     _lowerCamelCase   :					Union[str, Any]=2_56      ,     _lowerCamelCase   :					Dict=12      ,     _lowerCamelCase   :					str=12      ,     _lowerCamelCase   :					Dict=30_72      ,     _lowerCamelCase   :					Union[str, Any]="gelu"      ,     _lowerCamelCase   :					Optional[int]=0.1      ,     _lowerCamelCase   :					str=0.1      ,     _lowerCamelCase   :					Union[str, Any]=5_12      ,     _lowerCamelCase   :					int=2      ,     _lowerCamelCase   :					Optional[int]=0.02      ,     _lowerCamelCase   :					int=1E-12      ,     _lowerCamelCase   :					List[str]=True      ,     _lowerCamelCase   :					str=None      ,     _lowerCamelCase   :					Union[str, Any]=1      ,     _lowerCamelCase   :					str=0      ,     _lowerCamelCase   :					Dict=2      ,     **_lowerCamelCase   :					Optional[int]      ,     ):



					"""simple docstring"""

					super().__init__(pad_token_id=_lowerCamelCase      ,     bos_token_id=_lowerCamelCase      ,     eos_token_id=_lowerCamelCase      ,     **_lowerCamelCase       )

					A_  :				str	   =		vocab_size
					A_  :				Optional[Any]	   =		entity_vocab_size
					A_  :				Optional[Any]	   =		hidden_size
					A_  :				List[str]	   =		entity_emb_size
					A_  :				Union[str, Any]	   =		num_hidden_layers
					A_  :				Dict	   =		num_attention_heads
					A_  :				Union[str, Any]	   =		hidden_act
					A_  :				Dict	   =		intermediate_size
					A_  :				int	   =		hidden_dropout_prob
					A_  :				str	   =		attention_probs_dropout_prob
					A_  :				List[Any]	   =		max_position_embeddings
					A_  :				Optional[Any]	   =		type_vocab_size
					A_  :				Optional[int]	   =		initializer_range
					A_  :				str	   =		layer_norm_eps
					A_  :				List[str]	   =		use_entity_aware_attention
					A_  :				Optional[int]	   =		classifier_dropout





