


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


class        __lowerCamelCase      (				enum.Enum ):


				"""simple docstring"""







				a_:		Optional[Any]					      =	"""timm"""
				a_:		Tuple					      =	"""transformers"""

def 		snake_case_   (				lowercase__     :    Optional[Iterable[str]]       ,     lowercase__     :    Optional[Iterable[int]]       ,     lowercase__     :    Optional[Iterable[str]]     ):






				'''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(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 		snake_case_   (				lowercase__     :    Optional[List[str]]       ,     lowercase__     :    Optional[Union[List[int], Tuple[int]]]       ,     lowercase__     :    List[str]       ,     ):






				'''simple docstring'''






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

def 		snake_case_   (				lowercase__     :    Optional[List[str]]       ,     lowercase__     :    Optional[Union[List[int], Tuple[int]]]       ,     lowercase__     :    List[str]       ,     ):






				'''simple docstring'''






				verify_out_features_out_indices(out_features=lowercase__       ,     out_indices=lowercase__       ,     stage_names=lowercase__     )
				_lowerCAmelCase						,							_lowerCAmelCase  						=_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        __lowerCamelCase      :


				"""simple docstring"""







				a_:		Optional[BackboneType]					      =	None






				def        lowerCAmelCase__			(				self     :    int	,							lowerCamelCase_     :    Tuple					):
								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']
								_lowerCAmelCase  						=[stage["""module"""] for stage in self._backbone.feature_info.info]
								_lowerCAmelCase  						=[stage["""num_chs"""] for stage in self._backbone.feature_info.info]
								_lowerCAmelCase  						=self._backbone.feature_info.out_indices
								_lowerCAmelCase  						=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					)
								_lowerCAmelCase						,							_lowerCAmelCase  						=out_features, out_indices






				def        lowerCAmelCase__			(				self     :    Dict	,							lowerCamelCase_     :    Any					):
								_lowerCAmelCase  						=getattr(lowerCamelCase_	,							"""stage_names"""					)
								_lowerCAmelCase  						=getattr(lowerCamelCase_	,							"""out_features"""	,							lowerCamelCase_					)
								_lowerCAmelCase  						=getattr(lowerCamelCase_	,							"""out_indices"""	,							lowerCamelCase_					)

								_lowerCAmelCase  						=stage_names
								_lowerCAmelCase						,							_lowerCAmelCase  						=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
								_lowerCAmelCase  						=None






				def        lowerCAmelCase__			(				self     :    Any	,							lowerCamelCase_     :    Dict					):
								_lowerCAmelCase  						=config

								_lowerCAmelCase  						=getattr(lowerCamelCase_	,							"""use_timm_backbone"""	,							lowerCamelCase_					)
								_lowerCAmelCase  						=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        lowerCAmelCase__			(				self     :    str					):
								return self._out_features






				@out_features.setter
				def        lowerCAmelCase__			(				self     :    int	,							lowerCamelCase_     :    List[str]					):
								_lowerCAmelCase						,							_lowerCAmelCase  						=get_aligned_output_features_output_indices(
								    out_features=lowerCamelCase_	,							out_indices=lowerCamelCase_	,							stage_names=self.stage_names					)






				@property
				def        lowerCAmelCase__			(				self     :    int					):
								return self._out_indices






				@out_indices.setter
				def        lowerCAmelCase__			(				self     :    Optional[Any]	,							lowerCamelCase_     :    Union[Tuple[int], List[int]]					):
								_lowerCAmelCase						,							_lowerCAmelCase  						=get_aligned_output_features_output_indices(
								    out_features=lowerCamelCase_	,							out_indices=lowerCamelCase_	,							stage_names=self.stage_names					)






				@property
				def        lowerCAmelCase__			(				self     :    Optional[Any]					):
								# 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        lowerCAmelCase__			(				self     :    List[Any]					):
								return [self.out_feature_channels[name] for name in self.out_features]






				def        lowerCAmelCase__			(				self     :    Dict	,							*lowerCamelCase_     :    str	,							**lowerCamelCase_     :    Any					):
								_lowerCAmelCase  						=dict(inspect.signature(self.forward					).parameters					)
								_lowerCAmelCase  						={k: v for k, v in kwargs.items() if k in signature}
								return self(*lowerCamelCase_	,							**lowerCamelCase_					)






				def        lowerCAmelCase__			(				self     :    Tuple	,							lowerCamelCase_     :    Any	,							lowerCamelCase_     :    Optional[bool] = None	,							lowerCamelCase_     :    Optional[bool] = None	,							lowerCamelCase_     :    Optional[bool] = None	,							):
								raise NotImplementedError("""This method should be implemented by the derived class."""					)






				def        lowerCAmelCase__			(				self     :    List[str]					):
								_lowerCAmelCase  						=super().to_dict()
								_lowerCAmelCase  						=output.pop("""_out_features"""					)
								_lowerCAmelCase  						=output.pop("""_out_indices"""					)
								return output


class        __lowerCamelCase      :


				"""simple docstring"""







				@property
				def        lowerCAmelCase__			(				self     :    Tuple					):
								return self._out_features






				@out_features.setter
				def        lowerCAmelCase__			(				self     :    Any	,							lowerCamelCase_     :    List[str]					):
								_lowerCAmelCase						,							_lowerCAmelCase  						=get_aligned_output_features_output_indices(
								    out_features=lowerCamelCase_	,							out_indices=lowerCamelCase_	,							stage_names=self.stage_names					)






				@property
				def        lowerCAmelCase__			(				self     :    List[str]					):
								return self._out_indices






				@out_indices.setter
				def        lowerCAmelCase__			(				self     :    Tuple	,							lowerCamelCase_     :    Union[Tuple[int], List[int]]					):
								_lowerCAmelCase						,							_lowerCAmelCase  						=get_aligned_output_features_output_indices(
								    out_features=lowerCamelCase_	,							out_indices=lowerCamelCase_	,							stage_names=self.stage_names					)






				def        lowerCAmelCase__			(				self     :    List[str]					):
								_lowerCAmelCase  						=super().to_dict()
								_lowerCAmelCase  						=output.pop("""_out_features"""					)
								_lowerCAmelCase  						=output.pop("""_out_indices"""					)
								return output





from __future__ import annotations

__SCREAMING_SNAKE_CASE	:							Union[str, Any]           =  [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]


class        __lowerCamelCase      :


				"""simple docstring"""







				def __init__(				self     :    Dict	,							lowerCamelCase_     :    int					):
								_lowerCAmelCase  						=-1
								_lowerCAmelCase  						=-1
								_lowerCAmelCase  						=[-1] * length
								_lowerCAmelCase  						=None
								_lowerCAmelCase  						=None






				def __repr__(				self     :    Tuple					):
								return F"Node(min_value={self.minn} max_value={self.maxx})"

def 		snake_case_   (				lowercase__     :    list[int]     ):






				'''simple docstring'''






				_lowerCAmelCase  						=Node(len(lowercase__     )     )
				_lowerCAmelCase						,							_lowerCAmelCase  						=min(lowercase__     ), max(lowercase__     )
				# Leaf node case where the node contains only one unique value
				if root.minn == root.maxx:
								return root
				_lowerCAmelCase  						=(root.minn + root.maxx) // 2

				_lowerCAmelCase  						=[]
				_lowerCAmelCase  						=[]

				for index, num in enumerate(lowercase__     ):
								if num <= pivot:
												left_arr.append(lowercase__     )
								else:
												right_arr.append(lowercase__     )
								_lowerCAmelCase  						=len(lowercase__     )
				_lowerCAmelCase  						=build_tree(lowercase__     )
				_lowerCAmelCase  						=build_tree(lowercase__     )
				return root

def 		snake_case_   (				lowercase__     :    Node | None       ,     lowercase__     :    int       ,     lowercase__     :    int     ):






				'''simple docstring'''






				if index < 0 or node is None:
								return 0
				# Leaf node cases
				if node.minn == node.maxx:
								return index + 1 if node.minn == num else 0
				_lowerCAmelCase  						=(node.minn + node.maxx) // 2
				if num <= pivot:
								# go the left subtree and map index to the left subtree
								return rank_till_index(node.left       ,     lowercase__       ,     node.map_left[index] - 1     )
				else:
								# go to the right subtree and map index to the right subtree
								return rank_till_index(node.right       ,     lowercase__       ,     index - node.map_left[index]     )

def 		snake_case_   (				lowercase__     :    Node | None       ,     lowercase__     :    int       ,     lowercase__     :    int       ,     lowercase__     :    int     ):






				'''simple docstring'''






				if start > end:
								return 0
				_lowerCAmelCase  						=rank_till_index(lowercase__       ,     lowercase__       ,     lowercase__     )
				_lowerCAmelCase  						=rank_till_index(lowercase__       ,     lowercase__       ,     start - 1     )
				return rank_till_end - rank_before_start

def 		snake_case_   (				lowercase__     :    Node | None       ,     lowercase__     :    int       ,     lowercase__     :    int       ,     lowercase__     :    int     ):






				'''simple docstring'''






				if index > (end - start) or start > end or node is None:
								return -1
				# Leaf node case
				if node.minn == node.maxx:
								return node.minn
				# Number of elements in the left subtree in interval [start, end]
				_lowerCAmelCase  						=node.map_left[end] - (
				    node.map_left[start - 1] if start else 0
				)
				if num_elements_in_left_tree > index:
								return quantile(
								    node.left       ,     lowercase__       ,     (node.map_left[start - 1] if start else 0)       ,     node.map_left[end] - 1       ,     )
				else:
								return quantile(
								    node.right       ,     index - num_elements_in_left_tree       ,     start - (node.map_left[start - 1] if start else 0)       ,     end - node.map_left[end]       ,     )

def 		snake_case_   (				lowercase__     :    Node | None       ,     lowercase__     :    int       ,     lowercase__     :    int       ,     lowercase__     :    int       ,     lowercase__     :    int     ):






				'''simple docstring'''






				if (
				    start > end
				    or node is None
				    or start_num > end_num
				    or node.minn > end_num
				    or node.maxx < start_num
				):
								return 0
				if start_num <= node.minn and node.maxx <= end_num:
								return end - start + 1
				_lowerCAmelCase  						=range_counting(
				    node.left       ,     (node.map_left[start - 1] if start else 0)       ,     node.map_left[end] - 1       ,     lowercase__       ,     lowercase__       ,     )
				_lowerCAmelCase  						=range_counting(
				    node.right       ,     start - (node.map_left[start - 1] if start else 0)       ,     end - node.map_left[end]       ,     lowercase__       ,     lowercase__       ,     )
				return left + right


if __name__ == "__main__":
		import doctest

		doctest.testmod()

