




class 							__SCREAMING_SNAKE_CASE				:

					def __init__(							self					,			__lowercase   ):







						'''simple docstring'''




						lowerCamelCase_				:						List[str]				  =				val
						# Number of nodes in left subtree
						lowerCamelCase_				:						Tuple				  =				0
						lowerCamelCase_				:						Union[str, Any]				  =				None
						lowerCamelCase_				:						Any				  =				None
						lowerCamelCase_				:						Optional[Any]				  =				None





					def       lowercase_				(							self					,			__lowercase   ):







						'''simple docstring'''




						assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

						if self.val < other.val:
							lowerCamelCase_				:						List[str]				  =				self.right
							lowerCamelCase_				:						str				  =				None
							if self.right:
								lowerCamelCase_				:						Dict				  =				other
							lowerCamelCase_				:						Tuple				  =				other
							lowerCamelCase_				:						Any				  =				self.left_tree_size * 2 + 1
							return self
						else:
							lowerCamelCase_				:						int				  =				other.right
							lowerCamelCase_				:						Tuple				  =				None
							if other.right:
								lowerCamelCase_				:						Union[str, Any]				  =				self
							lowerCamelCase_				:						Optional[int]				  =				self
							lowerCamelCase_				:						List[str]				  =				other.left_tree_size * 2 + 1
							return other


class 							__SCREAMING_SNAKE_CASE				:

					def __init__(							self					,			__lowercase=None					,			__lowercase=None					,			__lowercase=0   ):







						'''simple docstring'''




						lowerCamelCase_				:						Tuple				  =				heap_size
						lowerCamelCase_				:						Optional[Any]				  =				bottom_root
						lowerCamelCase_				:						List[str]				  =				min_node

					def       lowercase_				(							self					,			__lowercase   ):







						'''simple docstring'''




						if other.size == 0:
							return None
						if self.size == 0:
							lowerCamelCase_				:						int				  =				other.size
							lowerCamelCase_				:						Tuple				  =				other.bottom_root
							lowerCamelCase_				:						List[str]				  =				other.min_node
							return None
						# Update size
						lowerCamelCase_				:						Tuple				  =				self.size + other.size

						# Update min.node
						if self.min_node.val > other.min_node.val:
							lowerCamelCase_				:						str				  =				other.min_node
						# Merge

						# Order roots by left_subtree_size
						lowerCamelCase_				:						Tuple				  =				[]
						lowerCamelCase_  ,     lowerCamelCase_				:						str				  =				self.bottom_root, other.bottom_root
						while i or j:
							if i and ((not j) or i.left_tree_size < j.left_tree_size):
								combined_roots_list.append((i, True)   )
								lowerCamelCase_				:						Tuple				  =				i.parent
							else:
								combined_roots_list.append((j, False)   )
								lowerCamelCase_				:						List[Any]				  =				j.parent
        # Insert links between them
						for i in range(len(__lowercase   ) - 1   ):
							if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
								lowerCamelCase_				:						Optional[int]				  =				combined_roots_list[i + 1][0]
								lowerCamelCase_				:						str				  =				combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
						lowerCamelCase_				:						Union[str, Any]				  =				combined_roots_list[0][0]
						while i.parent:
							if (
							    (i.left_tree_size == i.parent.left_tree_size) and (not i.parent.parent)
							) or (
							    i.left_tree_size == i.parent.left_tree_size
							    and i.left_tree_size != i.parent.parent.left_tree_size
							):
								# Neighbouring Nodes
								lowerCamelCase_				:						Any				  =				i.left
								lowerCamelCase_				:						Tuple				  =				i.parent.parent

								# Merging trees
								lowerCamelCase_				:						int				  =				i.merge_trees(i.parent   )

								# Updating links
								lowerCamelCase_				:						List[Any]				  =				previous_node
								lowerCamelCase_				:						Union[str, Any]				  =				next_node
								if previous_node:
									lowerCamelCase_				:						List[str]				  =				i
								if next_node:
									lowerCamelCase_				:						Tuple				  =				i
							else:
								lowerCamelCase_				:						Dict				  =				i.parent
        # Updating self.bottom_root
						while i.left:
							lowerCamelCase_				:						List[Any]				  =				i.left
						lowerCamelCase_				:						Optional[Any]				  =				i

						# Update other
						lowerCamelCase_				:						Tuple				  =				self.size
						lowerCamelCase_				:						Dict				  =				self.bottom_root
						lowerCamelCase_				:						Union[str, Any]				  =				self.min_node

						# Return the merged heap
						return self

					def       lowercase_				(							self					,			__lowercase   ):







						'''simple docstring'''




						if self.size == 0:
							lowerCamelCase_				:						Optional[Any]				  =				Node(__lowercase   )
							lowerCamelCase_				:						str				  =				1
							lowerCamelCase_				:						Union[str, Any]				  =				self.bottom_root
						else:
							# Create new node
							lowerCamelCase_				:						Optional[int]				  =				Node(__lowercase   )

							# Update size
							self.size += 1

							# update min_node
							if val < self.min_node.val:
								lowerCamelCase_				:						str				  =				new_node
							# Put new_node as a bottom_root in heap
							lowerCamelCase_				:						Tuple				  =				new_node
							lowerCamelCase_				:						Dict				  =				self.bottom_root
							lowerCamelCase_				:						int				  =				new_node

							# Consecutively merge roots with same left_tree_size
							while (
							    self.bottom_root.parent
							    and self.bottom_root.left_tree_size
							    == self.bottom_root.parent.left_tree_size
							):
								# Next node
								lowerCamelCase_				:						List[Any]				  =				self.bottom_root.parent.parent

								# Merge
								lowerCamelCase_				:						List[Any]				  =				self.bottom_root.merge_trees(self.bottom_root.parent   )

								# Update Links
								lowerCamelCase_				:						List[Any]				  =				next_node
								lowerCamelCase_				:						Union[str, Any]				  =				None
								if next_node:
									lowerCamelCase_				:						List[Any]				  =				self.bottom_root

					def       lowercase_				(							self   ):







						'''simple docstring'''




						return self.min_node.val

					def       lowercase_				(							self   ):







						'''simple docstring'''




						return self.size == 0

					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						Any				  =				self.min_node.val

						# Last element in heap corner case
						if self.size == 1:
							# Update size
							lowerCamelCase_				:						Union[str, Any]				  =				0

							# Update bottom root
							lowerCamelCase_				:						Any				  =				None

							# Update min_node
							lowerCamelCase_				:						int				  =				None

							return min_value
						# No right subtree corner case
						# The structure of the tree implies that this should be the bottom root
						# and there is at least one other root
						if self.min_node.right is None:
							# Update size
							self.size -= 1

							# Update bottom root
							lowerCamelCase_				:						int				  =				self.bottom_root.parent
							lowerCamelCase_				:						List[str]				  =				None

							# Update min_node
							lowerCamelCase_				:						Any				  =				self.bottom_root
							lowerCamelCase_				:						Optional[Any]				  =				self.bottom_root.parent
							while i:
								if i.val < self.min_node.val:
									lowerCamelCase_				:						Any				  =				i
								lowerCamelCase_				:						Optional[int]				  =				i.parent
							return min_value
						# General case
						# Find the BinomialHeap of the right subtree of min_node
						lowerCamelCase_				:						Dict				  =				self.min_node.right
						lowerCamelCase_				:						List[Any]				  =				None
						lowerCamelCase_				:						int				  =				bottom_of_new
						lowerCamelCase_				:						Any				  =				1

						# Size, min_node and bottom_root
						while bottom_of_new.left:
							lowerCamelCase_				:						Optional[Any]				  =				size_of_new * 2 + 1
							lowerCamelCase_				:						str				  =				bottom_of_new.left
							if bottom_of_new.val < min_of_new.val:
								lowerCamelCase_				:						Tuple				  =				bottom_of_new
        # Corner case of single root on top left path
						if (not self.min_node.left) and (not self.min_node.parent):
							lowerCamelCase_				:						Union[str, Any]				  =				size_of_new
							lowerCamelCase_				:						Any				  =				bottom_of_new
							lowerCamelCase_				:						List[str]				  =				min_of_new
							# print("Single root, multiple nodes case")
							return min_value
						# Remaining cases
						# Construct heap of right subtree
						lowerCamelCase_				:						Any				  =				BinomialHeap(
						    bottom_root=__lowercase					,			min_node=__lowercase					,			heap_size=__lowercase   )

						# Update size
						lowerCamelCase_				:						Tuple				  =				self.size - 1 - size_of_new

						# Neighbour nodes
						lowerCamelCase_				:						Dict				  =				self.min_node.left
						lowerCamelCase_				:						Optional[Any]				  =				self.min_node.parent

						# Initialize new bottom_root and min_node
						lowerCamelCase_				:						int				  =				previous_node or next_node
						lowerCamelCase_				:						int				  =				next_node

						# Update links of previous_node and search below for new min_node and
						# bottom_root
						if previous_node:
							lowerCamelCase_				:						Optional[Any]				  =				next_node

							# Update bottom_root and search for min_node below
							lowerCamelCase_				:						int				  =				previous_node
							lowerCamelCase_				:						Dict				  =				previous_node
							while self.bottom_root.left:
								lowerCamelCase_				:						int				  =				self.bottom_root.left
								if self.bottom_root.val < self.min_node.val:
									lowerCamelCase_				:						Any				  =				self.bottom_root
						if next_node:
							lowerCamelCase_				:						List[str]				  =				previous_node

							# Search for new min_node above min_node
							lowerCamelCase_				:						Union[str, Any]				  =				next_node
							while i:
								if i.val < self.min_node.val:
									lowerCamelCase_				:						Union[str, Any]				  =				i
								lowerCamelCase_				:						Dict				  =				i.parent
        # Merge heaps
						self.merge_heaps(__lowercase   )

						return min_value

					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						Optional[Any]				  =				self.bottom_root
						while top_root.parent:
							lowerCamelCase_				:						str				  =				top_root.parent
						# preorder
						lowerCamelCase_				:						int				  =				[]
						self.__traversal(__lowercase					,			__lowercase   )
						return heap_pre_order

					def       lowercase_				(							self					,			__lowercase					,			__lowercase					,			__lowercase=0   ):







						'''simple docstring'''




						if curr_node:
							preorder.append((curr_node.val, level)   )
							self.__traversal(curr_node.left					,			__lowercase					,			level + 1   )
							self.__traversal(curr_node.right					,			__lowercase					,			level + 1   )
						else:
							preorder.append(('#', level)   )





					def __str__(							self   ):







						'''simple docstring'''




						if self.is_empty():
							return ""
						lowerCamelCase_				:						int				  =				self.pre_order()

						return "\n".join(('-' * level + str(__lowercase   )) for value, level in preorder_heap   )


# Unit Tests
if __name__ == "__main__":
							import doctest

							doctest.testmod()







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


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

a_    :				Optional[Any]					=			{
    '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  SCREAMING_SNAKE_CASE_  ( SCREAMING_SNAKE_CASE__			):


  """simple docstring"""





  _a								=							"""vit-hybrid"""





  def __init__(  self	,  A=None	,  A=7_68	,  A=12	,  A=12	,  A=30_72	,  A="gelu"	,  A=0.0	,  A=0.0	,  A=0.02	,  A=1E-12	,  A=2_24	,  A=1	,  A=3	,  A=[1, 10_24, 24, 24]	,  A=True	,  **A	,  )		->   Union[str, Any]:





       '''simple docstring'''







       super().__init__(**A						)

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

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

       __magic_name__				=       backbone_featmap_shape
       __magic_name__				=       backbone_config
       __magic_name__				=       hidden_size
       __magic_name__				=       num_hidden_layers
       __magic_name__				=       num_attention_heads
       __magic_name__				=       intermediate_size
       __magic_name__				=       hidden_act
       __magic_name__				=       hidden_dropout_prob
       __magic_name__				=       attention_probs_dropout_prob
       __magic_name__				=       initializer_range
       __magic_name__				=       layer_norm_eps
       __magic_name__				=       image_size
       __magic_name__				=       patch_size
       __magic_name__				=       num_channels
       __magic_name__				=       qkv_bias







  def 			__A      (  self						)		->   Dict[str, any]:





       '''simple docstring'''







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