



'''simple docstring'''







import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union




class 				__lowerCAmelCase(							enum.Enum      ):
			__snake_case  :		Any		=      'timm'
			__snake_case  :		str		=      'transformers'







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     ):
		if stage_names is None:
				raise ValueError('Stage_names must be set for transformers backbones'     )

		if out_features is not None:
				if not isinstance(SCREAMING_SNAKE_CASE ,		(list,)     ):
						raise ValueError(F'out_features must be a list {type(SCREAMING_SNAKE_CASE     )}'     )
				if any(feat not in stage_names for feat in out_features     ):
						raise ValueError(F'out_features must be a subset of stage_names: {stage_names} got {out_features}'     )

		if out_indices is not None:
				if not isinstance(SCREAMING_SNAKE_CASE ,		(list, tuple)     ):
						raise ValueError(F'out_indices must be a list or tuple, got {type(SCREAMING_SNAKE_CASE     )}'     )
				if any(idx >= len(SCREAMING_SNAKE_CASE     ) for idx in out_indices     ):
						raise ValueError('out_indices must be valid indices for stage_names {stage_names}, got {out_indices}'     )

		if out_features is not None and out_indices is not None:
				if len(SCREAMING_SNAKE_CASE     ) != len(SCREAMING_SNAKE_CASE     ):
						raise ValueError('out_features and out_indices should have the same length if both are set'     )
				if out_features != [stage_names[idx] for idx in out_indices]:
						raise ValueError('out_features and out_indices should correspond to the same stages if both are set'     )







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		):
		if out_indices is None and out_features is None:
				SCREAMING_SNAKE_CASE_						:Dict										=      [len(SCREAMING_SNAKE_CASE     ) - 1]
				SCREAMING_SNAKE_CASE_						:Tuple										=      [stage_names[-1]]
		elif out_indices is None and out_features is not None:
				SCREAMING_SNAKE_CASE_						:Tuple										=      [stage_names.index(SCREAMING_SNAKE_CASE     ) for layer in out_features]
		elif out_features is None and out_indices is not None:
				SCREAMING_SNAKE_CASE_						:List[str]										=      [stage_names[idx] for idx in out_indices]
		return out_features, out_indices







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		):
		verify_out_features_out_indices(out_features=SCREAMING_SNAKE_CASE ,		out_indices=SCREAMING_SNAKE_CASE ,		stage_names=SCREAMING_SNAKE_CASE     )
		SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      _align_output_features_output_indices(
		    out_features=SCREAMING_SNAKE_CASE ,		out_indices=SCREAMING_SNAKE_CASE ,		stage_names=SCREAMING_SNAKE_CASE     )
		# Verify that the aligned out_features and out_indices are valid
		verify_out_features_out_indices(out_features=SCREAMING_SNAKE_CASE ,		out_indices=SCREAMING_SNAKE_CASE ,		stage_names=SCREAMING_SNAKE_CASE     )
		return output_features, output_indices




class 				__lowerCAmelCase:
			__snake_case  :		Optional[BackboneType]		=      None






			def 				_lowercase	(   self  :							List[Any]      ,       SCREAMING_SNAKE_CASE  :							Union[str, Any]	):




					"""simple docstring"""







					if getattr(self      ,       '_backbone'      ,       SCREAMING_SNAKE_CASE	) is None:
							raise ValueError('self._backbone must be set before calling _init_timm_backbone'	)

					# These will diagree with the defaults for the transformers models e.g. for resnet50
					# the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
					# the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
					SCREAMING_SNAKE_CASE_						:Tuple										=      [stage['module'] for stage in self._backbone.feature_info.info]
					SCREAMING_SNAKE_CASE_						:List[Any]										=      [stage['num_chs'] for stage in self._backbone.feature_info.info]
					SCREAMING_SNAKE_CASE_						:Dict										=      self._backbone.feature_info.out_indices
					SCREAMING_SNAKE_CASE_						:Tuple										=      self._backbone.feature_info.module_name()

					# We verify the out indices and out features are valid
					verify_out_features_out_indices(
					    out_features=SCREAMING_SNAKE_CASE      ,       out_indices=SCREAMING_SNAKE_CASE      ,       stage_names=self.stage_names	)
					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:str										=      out_features, out_indices






			def 				_lowercase	(   self  :							Optional[int]      ,       SCREAMING_SNAKE_CASE  :							Tuple	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[Any]										=      getattr(SCREAMING_SNAKE_CASE      ,       'stage_names'	)
					SCREAMING_SNAKE_CASE_						:Tuple										=      getattr(SCREAMING_SNAKE_CASE      ,       'out_features'      ,       SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:List[Any]										=      getattr(SCREAMING_SNAKE_CASE      ,       'out_indices'      ,       SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:Tuple										=      stage_names
					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:Tuple										=      get_aligned_output_features_output_indices(
					    out_features=SCREAMING_SNAKE_CASE      ,       out_indices=SCREAMING_SNAKE_CASE      ,       stage_names=SCREAMING_SNAKE_CASE	)
					# Number of channels for each stage. This is set in the transformer backbone model init
					SCREAMING_SNAKE_CASE_						:Dict										=      None






			def 				_lowercase	(   self  :							List[str]      ,       SCREAMING_SNAKE_CASE  :							Tuple	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Dict										=      config

					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      getattr(SCREAMING_SNAKE_CASE      ,       'use_timm_backbone'      ,       SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:Any										=      BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

					if self.backbone_type == BackboneType.TIMM:
							self._init_timm_backbone(SCREAMING_SNAKE_CASE	)
					elif self.backbone_type == BackboneType.TRANSFORMERS:
							self._init_transformers_backbone(SCREAMING_SNAKE_CASE	)
					else:
							raise ValueError(f'backbone_type {self.backbone_type} not supported.'	)






			@property
			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







					return self._out_features






			@out_features.setter
			def 				_lowercase	(   self  :							int      ,       SCREAMING_SNAKE_CASE  :							List[str]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:List[Any]										=      get_aligned_output_features_output_indices(
					    out_features=SCREAMING_SNAKE_CASE      ,       out_indices=SCREAMING_SNAKE_CASE      ,       stage_names=self.stage_names	)






			@property
			def 				_lowercase	(   self  :							Tuple	):




					"""simple docstring"""







					return self._out_indices






			@out_indices.setter
			def 				_lowercase	(   self  :							Tuple      ,       SCREAMING_SNAKE_CASE  :							Union[Tuple[int], List[int]]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:str										=      get_aligned_output_features_output_indices(
					    out_features=SCREAMING_SNAKE_CASE      ,       out_indices=SCREAMING_SNAKE_CASE      ,       stage_names=self.stage_names	)






			@property
			def 				_lowercase	(   self  :							Optional[int]	):




					"""simple docstring"""







					return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names	)}






			@property
			def 				_lowercase	(   self  :							Optional[Any]	):




					"""simple docstring"""







					return [self.out_feature_channels[name] for name in self.out_features]






			def 				_lowercase	(   self  :							List[str]      ,       *SCREAMING_SNAKE_CASE  :							Tuple      ,       **SCREAMING_SNAKE_CASE  :							str	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Tuple										=      dict(inspect.signature(self.forward	).parameters	)
					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      {k: v for k, v in kwargs.items() if k in signature}
					return self(*SCREAMING_SNAKE_CASE      ,       **SCREAMING_SNAKE_CASE	)






			def 				_lowercase	(   self  :							Optional[Any]      ,       SCREAMING_SNAKE_CASE  :							Any      ,       SCREAMING_SNAKE_CASE  :							Optional[bool] = None      ,       SCREAMING_SNAKE_CASE  :							Optional[bool] = None      ,       SCREAMING_SNAKE_CASE  :							Optional[bool] = None      ,       ):




					"""simple docstring"""







					raise NotImplementedError('This method should be implemented by the derived class.'	)






			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Dict										=      super().to_dict()
					SCREAMING_SNAKE_CASE_						:List[str]										=      output.pop('_out_features'	)
					SCREAMING_SNAKE_CASE_						:Optional[int]										=      output.pop('_out_indices'	)
					return output




class 				__lowerCAmelCase:






			@property
			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







					return self._out_features






			@out_features.setter
			def 				_lowercase	(   self  :							List[str]      ,       SCREAMING_SNAKE_CASE  :							List[str]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:Optional[int]										=      get_aligned_output_features_output_indices(
					    out_features=SCREAMING_SNAKE_CASE      ,       out_indices=SCREAMING_SNAKE_CASE      ,       stage_names=self.stage_names	)






			@property
			def 				_lowercase	(   self  :							List[Any]	):




					"""simple docstring"""







					return self._out_indices






			@out_indices.setter
			def 				_lowercase	(   self  :							Optional[int]      ,       SCREAMING_SNAKE_CASE  :							Union[Tuple[int], List[int]]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:List[Any]										=      get_aligned_output_features_output_indices(
					    out_features=SCREAMING_SNAKE_CASE      ,       out_indices=SCREAMING_SNAKE_CASE      ,       stage_names=self.stage_names	)






			def 				_lowercase	(   self  :							str	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:str										=      super().to_dict()
					SCREAMING_SNAKE_CASE_						:Tuple										=      output.pop('_out_features'	)
					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      output.pop('_out_indices'	)
					return output

"""simple docstring"""


import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


lowerCAmelCase_:       Union[str, Any]			     =       logging.get_logger(__name__)

lowerCAmelCase_:       Dict			     =       {
    "google/vit-hybrid-base-bit-384": "https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}






class  a__     ( _a						):
   snake_case_				=   "vit-hybrid"


   def __init__(  self,					_UpperCAmelCase=None,					_UpperCAmelCase=768,					_UpperCAmelCase=12,					_UpperCAmelCase=12,					_UpperCAmelCase=3072,					_UpperCAmelCase="gelu",					_UpperCAmelCase=0.0,					_UpperCAmelCase=0.0,					_UpperCAmelCase=0.02,					_UpperCAmelCase=1E-12,					_UpperCAmelCase=224,					_UpperCAmelCase=1,					_UpperCAmelCase=3,					_UpperCAmelCase=[1, 1024, 24, 24],					_UpperCAmelCase=True,					**_UpperCAmelCase,					):
        '''simple docstring'''



        super().__init__(**_UpperCAmelCase	)

        if backbone_config is None:
             logger.info("`backbone_config` is `None`. Initializing the config with a `BiT` backbone."	)
             lowercase__								=				{
                 "global_padding": "same",
                 "layer_type": "bottleneck",
                 "depths": [3, 4, 9],
                 "out_features": ["stage3"],
                 "embedding_dynamic_padding": True,
             }

        if isinstance(_UpperCAmelCase,					_UpperCAmelCase	):
             if "model_type" in backbone_config:
                  lowercase__								=				CONFIG_MAPPING[backbone_config["model_type"]]
             else:
                  logger.info(
                      "`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."	)
                  lowercase__								=				BitConfig
             lowercase__								=				backbone_config_class(**_UpperCAmelCase	)

        lowercase__								=				backbone_featmap_shape
        lowercase__								=				backbone_config
        lowercase__								=				hidden_size
        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


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				copy.deepcopy(self.__dict__	)
        lowercase__								=				self.backbone_config.to_dict()
        lowercase__								=				self.__class__.model_type
        return output




