





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




class   _UpperCAmelCase	(   enum.Enum					):
					__A          =   "timm"
					__A          =   "transformers"



def     a						(      _lowercase   :     Optional[Iterable[str]] ,						_lowercase   :     Optional[Iterable[int]] ,						_lowercase   :     Optional[Iterable[str]]       )     ->List[str]:
		if stage_names is None:
				raise ValueError("""Stage_names must be set for transformers backbones"""       )

		if out_features is not None:
				if not isinstance(_lowercase ,						(list,)       ):
						raise ValueError(F"""out_features must be a list {type(_lowercase       )}"""       )
				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(_lowercase ,						(list, tuple)       ):
						raise ValueError(F"""out_indices must be a list or tuple, got {type(_lowercase       )}"""       )
				if any(idx >= len(_lowercase       ) 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(_lowercase       ) != len(_lowercase       ):
						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     a						(      _lowercase   :     Optional[List[str]] ,						_lowercase   :     Optional[Union[List[int], Tuple[int]]] ,						_lowercase   :     List[str] ,						)     ->Optional[int]:
		if out_indices is None and out_features is None:
				UpperCamelCase__         =	[len(_lowercase       ) - 1]
				UpperCamelCase__         =	[stage_names[-1]]
		elif out_indices is None and out_features is not None:
				UpperCamelCase__         =	[stage_names.index(_lowercase       ) 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     a						(      _lowercase   :     Optional[List[str]] ,						_lowercase   :     Optional[Union[List[int], Tuple[int]]] ,						_lowercase   :     List[str] ,						)     ->Tuple[List[str], List[int]]:
		verify_out_features_out_indices(out_features=_lowercase ,						out_indices=_lowercase ,						stage_names=_lowercase       )
		UpperCamelCase__  ,			UpperCamelCase__         =	_align_output_features_output_indices(
		    out_features=_lowercase ,						out_indices=_lowercase ,						stage_names=_lowercase       )
		# Verify that the aligned out_features and out_indices are valid
		verify_out_features_out_indices(out_features=_lowercase ,						out_indices=_lowercase ,						stage_names=_lowercase       )
		return output_features, output_indices




class   _UpperCAmelCase	:
					__A          =   None




					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  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__  ,			UpperCamelCase__         =	out_features, out_indices




					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  None:
							UpperCamelCase__         =	getattr(__lowerCAmelCase    ,      """stage_names"""       )
							UpperCamelCase__         =	getattr(__lowerCAmelCase    ,      """out_features"""    ,      __lowerCAmelCase       )
							UpperCamelCase__         =	getattr(__lowerCAmelCase    ,      """out_indices"""    ,      __lowerCAmelCase       )

							UpperCamelCase__         =	stage_names
							UpperCamelCase__  ,			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 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  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 	snake_case_		(						self       )						->  List[str]:
							return self._out_features




					@out_features.setter
					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  Optional[Any]:
							UpperCamelCase__  ,			UpperCamelCase__         =	get_aligned_output_features_output_indices(
							    out_features=__lowerCAmelCase    ,      out_indices=__lowerCAmelCase    ,      stage_names=self.stage_names       )




					@property
					def 	snake_case_		(						self       )						->  int:
							return self._out_indices




					@out_indices.setter
					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  List[Any]:
							UpperCamelCase__  ,			UpperCamelCase__         =	get_aligned_output_features_output_indices(
							    out_features=__lowerCAmelCase    ,      out_indices=__lowerCAmelCase    ,      stage_names=self.stage_names       )




					@property
					def 	snake_case_		(						self       )						->  int:
							# the current backbones will output the number of channels for each stage
							# even if that stage is not in the out_features list.
							return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names       )}




					@property
					def 	snake_case_		(						self       )						->  Optional[Any]:
							return [self.out_feature_channels[name] for name in self.out_features]




					def 	snake_case_		(						self    ,      *__lowerCAmelCase    ,      **__lowerCAmelCase       )						->  str:
							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 	snake_case_		(						self    ,      __lowerCAmelCase    ,      __lowerCAmelCase = None    ,      __lowerCAmelCase = None    ,      __lowerCAmelCase = None    ,      )						->  Union[str, Any]:
							raise NotImplementedError("""This method should be implemented by the derived class."""       )




					def 	snake_case_		(						self       )						->  Tuple:
							UpperCamelCase__         =	super().to_dict()
							UpperCamelCase__         =	output.pop("""_out_features"""       )
							UpperCamelCase__         =	output.pop("""_out_indices"""       )
							return output




class   _UpperCAmelCase	:




					@property
					def 	snake_case_		(						self       )						->  Optional[Any]:
							return self._out_features




					@out_features.setter
					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  Any:
							UpperCamelCase__  ,			UpperCamelCase__         =	get_aligned_output_features_output_indices(
							    out_features=__lowerCAmelCase    ,      out_indices=__lowerCAmelCase    ,      stage_names=self.stage_names       )




					@property
					def 	snake_case_		(						self       )						->  Dict:
							return self._out_indices




					@out_indices.setter
					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  Optional[int]:
							UpperCamelCase__  ,			UpperCamelCase__         =	get_aligned_output_features_output_indices(
							    out_features=__lowerCAmelCase    ,      out_indices=__lowerCAmelCase    ,      stage_names=self.stage_names       )




					def 	snake_case_		(						self       )						->  Optional[int]:
							UpperCamelCase__         =	super().to_dict()
							UpperCamelCase__         =	output.pop("""_out_features"""       )
							UpperCamelCase__         =	output.pop("""_out_indices"""       )
							return output












import warnings

from .generation import FlaxGenerationMixin




class   _UpperCAmelCase	(   _lowercase					):
					# warning at import time
					warnings.warn(
					    "Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will "
					    "be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead." ,       _lowercase ,       )





