




import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union
class      _UpperCamelCase (			enum.Enum						):
      UpperCAmelCase_            =						'timm'
      UpperCAmelCase_            =						'transformers'



def   lowerCAmelCase						(						_lowerCAmelCase							:				Union[str, Any]  ,							_lowerCAmelCase							:				Optional[int]  ,							_lowerCAmelCase							:				Dict		):




 """simple docstring"""







 if stage_names is None:
  raise ValueError("Stage_names must be set for transformers backbones"		)

 if out_features is not None:
  if not isinstance(_lowerCAmelCase  ,							(list,)		):
   raise ValueError(F'''out_features must be a list {type(_lowerCAmelCase		)}'''		)
  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(_lowerCAmelCase  ,							(list, tuple)		):
   raise ValueError(F'''out_indices must be a list or tuple, got {type(_lowerCAmelCase		)}'''		)
  if any(idx >= len(_lowerCAmelCase		) 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(_lowerCAmelCase		) != len(_lowerCAmelCase		):
   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   lowerCAmelCase						(						_lowerCAmelCase							:				Union[str, Any]  ,							_lowerCAmelCase							:				List[str]  ,							_lowerCAmelCase							:				Optional[Any]  ,							):




 """simple docstring"""







 if out_indices is None and out_features is None:
  UpperCAmelCase__								=  [len(_lowerCAmelCase		) - 1]
  UpperCAmelCase__								=  [stage_names[-1]]
 elif out_indices is None and out_features is not None:
  UpperCAmelCase__								=  [stage_names.index(_lowerCAmelCase		) for layer in out_features]
 elif out_features is None and out_indices is not None:
  UpperCAmelCase__								=  [stage_names[idx] for idx in out_indices]
 return out_features, out_indices



def   lowerCAmelCase						(						_lowerCAmelCase							:				Union[str, Any]  ,							_lowerCAmelCase							:				Tuple  ,							_lowerCAmelCase							:				Optional[Any]  ,							):




 """simple docstring"""







 verify_out_features_out_indices(out_features=_lowerCAmelCase  ,							out_indices=_lowerCAmelCase  ,							stage_names=_lowerCAmelCase		)
 UpperCAmelCase__								=  _align_output_features_output_indices(
     out_features=_lowerCAmelCase  ,							out_indices=_lowerCAmelCase  ,							stage_names=_lowerCAmelCase		)
 # Verify that the aligned out_features and out_indices are valid
 verify_out_features_out_indices(out_features=_lowerCAmelCase  ,							out_indices=_lowerCAmelCase  ,							stage_names=_lowerCAmelCase		)
 return output_features, output_indices
class      _UpperCamelCase :
      UpperCAmelCase_            =						None
      def 		UpperCAmelCase_  (     self				:Optional[Any]	, lowerCamelCase				:Optional[Any] )       ->     None:




       if getattr(self	, "_backbone"	, lowerCamelCase ) 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']
       UpperCAmelCase__								=  [stage["""module"""] for stage in self._backbone.feature_info.info]
       UpperCAmelCase__								=  [stage["""num_chs"""] for stage in self._backbone.feature_info.info]
       UpperCAmelCase__								=  self._backbone.feature_info.out_indices
       UpperCAmelCase__								=  self._backbone.feature_info.module_name()

       # We verify the out indices and out features are valid
       verify_out_features_out_indices(
           out_features=lowerCamelCase	, out_indices=lowerCamelCase	, stage_names=self.stage_names )
       UpperCAmelCase__								=  out_features, out_indices
      def 		UpperCAmelCase_  (     self				:List[Any]	, lowerCamelCase				:Any )       ->     None:
       UpperCAmelCase__								=  getattr(lowerCamelCase	, "stage_names" )
       UpperCAmelCase__								=  getattr(lowerCamelCase	, "out_features"	, lowerCamelCase )
       UpperCAmelCase__								=  getattr(lowerCamelCase	, "out_indices"	, lowerCamelCase )

       UpperCAmelCase__								=  stage_names
       UpperCAmelCase__								=  get_aligned_output_features_output_indices(
           out_features=lowerCamelCase	, out_indices=lowerCamelCase	, stage_names=lowerCamelCase )
       # Number of channels for each stage. This is set in the transformer backbone model init
       UpperCAmelCase__								=  None
      def 		UpperCAmelCase_  (     self				:Optional[int]	, lowerCamelCase				:Any )       ->     None:
       UpperCAmelCase__								=  config

       UpperCAmelCase__								=  getattr(lowerCamelCase	, "use_timm_backbone"	, lowerCamelCase )
       UpperCAmelCase__								=  BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

       if self.backbone_type == BackboneType.TIMM:
        self._init_timm_backbone(lowerCamelCase )
       elif self.backbone_type == BackboneType.TRANSFORMERS:
        self._init_transformers_backbone(lowerCamelCase )
       else:
        raise ValueError(f'''backbone_type {self.backbone_type} not supported.''' )
      @property
      def 		UpperCAmelCase_  (     self				:List[str] )       ->     int:
       return self._out_features
      @out_features.setter
      def 		UpperCAmelCase_  (     self				:Union[str, Any]	, lowerCamelCase				:List[str] )       ->     Dict:
       UpperCAmelCase__								=  get_aligned_output_features_output_indices(
           out_features=lowerCamelCase	, out_indices=lowerCamelCase	, stage_names=self.stage_names )
      @property
      def 		UpperCAmelCase_  (     self				:Union[str, Any] )       ->     str:
       return self._out_indices
      @out_indices.setter
      def 		UpperCAmelCase_  (     self				:Tuple	, lowerCamelCase				:Union[Tuple[int], List[int]] )       ->     Union[str, Any]:
       UpperCAmelCase__								=  get_aligned_output_features_output_indices(
           out_features=lowerCamelCase	, out_indices=lowerCamelCase	, stage_names=self.stage_names )
      @property
      def 		UpperCAmelCase_  (     self				:Optional[Any] )       ->     List[Any]:
       return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names )}
      @property
      def 		UpperCAmelCase_  (     self				:Dict )       ->     List[str]:
       return [self.out_feature_channels[name] for name in self.out_features]
      def 		UpperCAmelCase_  (     self				:Optional[Any]	, *lowerCamelCase				:Optional[Any]	, **lowerCamelCase				:Tuple )       ->     Union[str, Any]:
       UpperCAmelCase__								=  dict(inspect.signature(self.forward ).parameters )
       UpperCAmelCase__								=  {k: v for k, v in kwargs.items() if k in signature}
       return self(*lowerCamelCase	, **lowerCamelCase )
      def 		UpperCAmelCase_  (     self				:str	, lowerCamelCase				:Tuple	, lowerCamelCase				:Optional[bool] = None	, lowerCamelCase				:Optional[bool] = None	, lowerCamelCase				:Optional[bool] = None	, )       ->     List[Any]:
       raise NotImplementedError("This method should be implemented by the derived class." )







      def 		UpperCAmelCase_  (     self				:str )       ->     List[Any]:
       UpperCAmelCase__								=  super().to_dict()
       UpperCAmelCase__								=  output.pop("_out_features" )
       UpperCAmelCase__								=  output.pop("_out_indices" )
       return output



class      _UpperCamelCase :
      @property
      def 		UpperCAmelCase_  (     self				:Optional[int] )       ->     List[str]:
       return self._out_features
      @out_features.setter
      def 		UpperCAmelCase_  (     self				:Any	, lowerCamelCase				:List[str] )       ->     int:
       UpperCAmelCase__								=  get_aligned_output_features_output_indices(
           out_features=lowerCamelCase	, out_indices=lowerCamelCase	, stage_names=self.stage_names )
      @property
      def 		UpperCAmelCase_  (     self				:List[str] )       ->     Optional[int]:
       return self._out_indices
      @out_indices.setter
      def 		UpperCAmelCase_  (     self				:str	, lowerCamelCase				:Union[Tuple[int], List[int]] )       ->     Optional[int]:
       UpperCAmelCase__								=  get_aligned_output_features_output_indices(
           out_features=lowerCamelCase	, out_indices=lowerCamelCase	, stage_names=self.stage_names )







      def 		UpperCAmelCase_  (     self				:Tuple )       ->     int:
       UpperCAmelCase__								=  super().to_dict()
       UpperCAmelCase__								=  output.pop("_out_features" )
       UpperCAmelCase__								=  output.pop("_out_indices" )
       return output






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCAmelCase  :				Dict						=				logging.get_logger(__name__)

_lowerCAmelCase  :				Optional[int]						=				{
    "google/rembert": "https://huggingface.co/google/rembert/resolve/main/config.json",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}
class      _UpperCamelCase (			lowerCAmelCase						):
      UpperCAmelCase_            =						"""rembert"""
      def __init__(     self				:Union[str, Any]	, lowerCamelCase				:Union[str, Any]=25_0300	, lowerCamelCase				:Optional[Any]=1152	, lowerCamelCase				:Optional[int]=32	, lowerCamelCase				:Union[str, Any]=18	, lowerCamelCase				:str=256	, lowerCamelCase				:Any=1664	, lowerCamelCase				:Any=4608	, lowerCamelCase				:List[str]="gelu"	, lowerCamelCase				:Optional[Any]=0.0	, lowerCamelCase				:Optional[int]=0.0	, lowerCamelCase				:Dict=0.1	, lowerCamelCase				:List[str]=512	, lowerCamelCase				:int=2	, lowerCamelCase				:str=0.02	, lowerCamelCase				:Optional[int]=1e-12	, lowerCamelCase				:List[Any]=True	, lowerCamelCase				:Optional[Any]=0	, lowerCamelCase				:Optional[Any]=312	, lowerCamelCase				:int=313	, **lowerCamelCase				:Dict	, )       ->     Any:
       super().__init__(pad_token_id=lowerCamelCase	, bos_token_id=lowerCamelCase	, eos_token_id=lowerCamelCase	, **lowerCamelCase )

       UpperCAmelCase__								=  vocab_size
       UpperCAmelCase__								=  input_embedding_size
       UpperCAmelCase__								=  output_embedding_size
       UpperCAmelCase__								=  max_position_embeddings
       UpperCAmelCase__								=  hidden_size
       UpperCAmelCase__								=  num_hidden_layers
       UpperCAmelCase__								=  num_attention_heads
       UpperCAmelCase__								=  intermediate_size
       UpperCAmelCase__								=  hidden_act
       UpperCAmelCase__								=  hidden_dropout_prob
       UpperCAmelCase__								=  attention_probs_dropout_prob
       UpperCAmelCase__								=  classifier_dropout_prob
       UpperCAmelCase__								=  initializer_range
       UpperCAmelCase__								=  type_vocab_size
       UpperCAmelCase__								=  layer_norm_eps
       UpperCAmelCase__								=  use_cache
       UpperCAmelCase__								=  False



class      _UpperCamelCase (			lowerCAmelCase						):
      @property
      def 		UpperCAmelCase_  (     self				:List[Any] )       ->     Mapping[str, Mapping[int, str]]:
       if self.task == "multiple-choice":
        UpperCAmelCase__								=  {0: "batch", 1: "choice", 2: "sequence"}
       else:
        UpperCAmelCase__								=  {0: "batch", 1: "sequence"}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
               ("token_type_ids", dynamic_axis),
           ] )







      @property
      def 		UpperCAmelCase_  (     self				:Union[str, Any] )       ->     float:
       return 1e-4





