class        a_				:






	'''simple docstring'''






	def __init__(    self      :						Optional[Any]    ,					lowercase__      :						int):







								'''simple docstring'''



								lowerCAmelCase__  			=      val
								# Number of nodes in left subtree
								lowerCAmelCase__  			=      0
								lowerCAmelCase__  			=      None
								lowerCAmelCase__  			=      None
								lowerCAmelCase__  			=      None




	def 	__snake_case		(    self      :						str    ,					lowercase__      :						str):







								'''simple docstring'''



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

								if self.val < other.val:
															lowerCAmelCase__  			=      self.right
															lowerCAmelCase__  			=      None
															if self.right:
																						lowerCAmelCase__  			=      other
															lowerCAmelCase__  			=      other
															lowerCAmelCase__  			=      self.left_tree_size * 2 + 1
															return self
								else:
															lowerCAmelCase__  			=      other.right
															lowerCAmelCase__  			=      None
															if other.right:
																						lowerCAmelCase__  			=      self
															lowerCAmelCase__  			=      self
															lowerCAmelCase__  			=      other.left_tree_size * 2 + 1
															return other






class        a_				:






	'''simple docstring'''






	def __init__(    self      :						Any    ,					lowercase__      :						Dict=None    ,					lowercase__      :						List[str]=None    ,					lowercase__      :						List[str]=0):







								'''simple docstring'''



								lowerCAmelCase__  			=      heap_size
								lowerCAmelCase__  			=      bottom_root
								lowerCAmelCase__  			=      min_node




	def 	__snake_case		(    self      :						Optional[Any]    ,					lowercase__      :						Dict):







								'''simple docstring'''



								if other.size == 0:
															return None
								if self.size == 0:
															lowerCAmelCase__  			=      other.size
															lowerCAmelCase__  			=      other.bottom_root
															lowerCAmelCase__  			=      other.min_node
															return None
								# Update size
								lowerCAmelCase__  			=      self.size + other.size

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

								# Order roots by left_subtree_size
								lowerCAmelCase__  			=      []
								lowerCAmelCase__			,      lowerCAmelCase__  			=      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__  			=      i.parent
															else:
																						combined_roots_list.append((j, False))
																						lowerCAmelCase__  			=      j.parent
        # Insert links between them
								for i in range(len(lowerCAmelCase_) - 1):
															if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
																						lowerCAmelCase__  			=      combined_roots_list[i + 1][0]
																						lowerCAmelCase__  			=      combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
								lowerCAmelCase__  			=      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__  			=      i.left
																						lowerCAmelCase__  			=      i.parent.parent

																						# Merging trees
																						lowerCAmelCase__  			=      i.merge_trees(i.parent)

																						# Updating links
																						lowerCAmelCase__  			=      previous_node
																						lowerCAmelCase__  			=      next_node
																						if previous_node:
																													lowerCAmelCase__  			=      i
																						if next_node:
																													lowerCAmelCase__  			=      i
															else:
																						lowerCAmelCase__  			=      i.parent
        # Updating self.bottom_root
								while i.left:
															lowerCAmelCase__  			=      i.left
								lowerCAmelCase__  			=      i

								# Update other
								lowerCAmelCase__  			=      self.size
								lowerCAmelCase__  			=      self.bottom_root
								lowerCAmelCase__  			=      self.min_node

								# Return the merged heap
								return self




	def 	__snake_case		(    self      :						Optional[int]    ,					lowercase__      :						List[Any]):







								'''simple docstring'''



								if self.size == 0:
															lowerCAmelCase__  			=      Node(lowerCAmelCase_)
															lowerCAmelCase__  			=      1
															lowerCAmelCase__  			=      self.bottom_root
								else:
															# Create new node
															lowerCAmelCase__  			=      Node(lowerCAmelCase_)

															# Update size
															self.size += 1

															# update min_node
															if val < self.min_node.val:
																						lowerCAmelCase__  			=      new_node
															# Put new_node as a bottom_root in heap
															lowerCAmelCase__  			=      new_node
															lowerCAmelCase__  			=      self.bottom_root
															lowerCAmelCase__  			=      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__  			=      self.bottom_root.parent.parent

																						# Merge
																						lowerCAmelCase__  			=      self.bottom_root.merge_trees(self.bottom_root.parent)

																						# Update Links
																						lowerCAmelCase__  			=      next_node
																						lowerCAmelCase__  			=      None
																						if next_node:
																													lowerCAmelCase__  			=      self.bottom_root




	def 	__snake_case		(    self      :						Dict):







								'''simple docstring'''



								return self.min_node.val




	def 	__snake_case		(    self      :						List[Any]):







								'''simple docstring'''



								return self.size == 0




	def 	__snake_case		(    self      :						Optional[int]):







								'''simple docstring'''



								lowerCAmelCase__  			=      self.min_node.val

								# Last element in heap corner case
								if self.size == 1:
															# Update size
															lowerCAmelCase__  			=      0

															# Update bottom root
															lowerCAmelCase__  			=      None

															# Update min_node
															lowerCAmelCase__  			=      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__  			=      self.bottom_root.parent
															lowerCAmelCase__  			=      None

															# Update min_node
															lowerCAmelCase__  			=      self.bottom_root
															lowerCAmelCase__  			=      self.bottom_root.parent
															while i:
																						if i.val < self.min_node.val:
																													lowerCAmelCase__  			=      i
																						lowerCAmelCase__  			=      i.parent
															return min_value
								# General case
								# Find the BinomialHeap of the right subtree of min_node
								lowerCAmelCase__  			=      self.min_node.right
								lowerCAmelCase__  			=      None
								lowerCAmelCase__  			=      bottom_of_new
								lowerCAmelCase__  			=      1

								# Size, min_node and bottom_root
								while bottom_of_new.left:
															lowerCAmelCase__  			=      size_of_new * 2 + 1
															lowerCAmelCase__  			=      bottom_of_new.left
															if bottom_of_new.val < min_of_new.val:
																						lowerCAmelCase__  			=      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__  			=      size_of_new
															lowerCAmelCase__  			=      bottom_of_new
															lowerCAmelCase__  			=      min_of_new
															# print("Single root, multiple nodes case")
															return min_value
								# Remaining cases
								# Construct heap of right subtree
								lowerCAmelCase__  			=      BinomialHeap(
								    bottom_root=lowerCAmelCase_    ,					min_node=lowerCAmelCase_    ,					heap_size=lowerCAmelCase_)

								# Update size
								lowerCAmelCase__  			=      self.size - 1 - size_of_new

								# Neighbour nodes
								lowerCAmelCase__  			=      self.min_node.left
								lowerCAmelCase__  			=      self.min_node.parent

								# Initialize new bottom_root and min_node
								lowerCAmelCase__  			=      previous_node or next_node
								lowerCAmelCase__  			=      next_node

								# Update links of previous_node and search below for new min_node and
								# bottom_root
								if previous_node:
															lowerCAmelCase__  			=      next_node

															# Update bottom_root and search for min_node below
															lowerCAmelCase__  			=      previous_node
															lowerCAmelCase__  			=      previous_node
															while self.bottom_root.left:
																						lowerCAmelCase__  			=      self.bottom_root.left
																						if self.bottom_root.val < self.min_node.val:
																													lowerCAmelCase__  			=      self.bottom_root
								if next_node:
															lowerCAmelCase__  			=      previous_node

															# Search for new min_node above min_node
															lowerCAmelCase__  			=      next_node
															while i:
																						if i.val < self.min_node.val:
																													lowerCAmelCase__  			=      i
																						lowerCAmelCase__  			=      i.parent
        # Merge heaps
								self.merge_heaps(lowerCAmelCase_)

								return min_value




	def 	__snake_case		(    self      :						Tuple):







								'''simple docstring'''



								lowerCAmelCase__  			=      self.bottom_root
								while top_root.parent:
															lowerCAmelCase__  			=      top_root.parent
								# preorder
								lowerCAmelCase__  			=      []
								self.__traversal(lowerCAmelCase_    ,					lowerCAmelCase_)
								return heap_pre_order




	def 	__snake_case		(    self      :						List[Any]    ,					lowercase__      :						List[str]    ,					lowercase__      :						int    ,					lowercase__      :						Union[str, Any]=0):







								'''simple docstring'''



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




	def __str__(    self      :						str):







								'''simple docstring'''



								if self.is_empty():
															return ""
								lowerCAmelCase__  			=      self.pre_order()

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


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

				doctest.testmod()

import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class        a_				(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 UpperCAmelCase_							=      ['image_processor', 'tokenizer']
 UpperCAmelCase_							=      'LayoutLMv2ImageProcessor'
 UpperCAmelCase_							=      ('LayoutLMv2Tokenizer', 'LayoutLMv2TokenizerFast')




 def __init__(    self      :						List[Any]    ,					lowercase__      :						List[Any]=None    ,					lowercase__      :						int=None    ,					**lowercase__      :						Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__  			=      None
        if "feature_extractor" in kwargs:
               warnings.warn(
                   'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                   ' instead.'    ,					lowercase__    ,					)
               lowerCAmelCase__  			=      kwargs.pop('feature_extractor')

        lowerCAmelCase__  			=      image_processor if image_processor is not None else feature_extractor
        if image_processor is None:
               raise ValueError('You need to specify an `image_processor`.')
        if tokenizer is None:
               raise ValueError('You need to specify a `tokenizer`.')

        super().__init__(lowercase__    ,					lowercase__)




 def __call__(    self      :						Any    ,					lowercase__      :						Union[str, Any]    ,					lowercase__      :						Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None    ,					lowercase__      :						Optional[Union[PreTokenizedInput, List[PreTokenizedInput]]] = None    ,					lowercase__      :						Union[List[List[int]], List[List[List[int]]]] = None    ,					lowercase__      :						Optional[Union[List[int], List[List[int]]]] = None    ,					lowercase__      :						bool = True    ,					lowercase__      :						Union[bool, str, PaddingStrategy] = False    ,					lowercase__      :						Union[bool, str, TruncationStrategy] = False    ,					lowercase__      :						Optional[int] = None    ,					lowercase__      :						int = 0    ,					lowercase__      :						Optional[int] = None    ,					lowercase__      :						Optional[bool] = None    ,					lowercase__      :						Optional[bool] = None    ,					lowercase__      :						bool = False    ,					lowercase__      :						bool = False    ,					lowercase__      :						bool = False    ,					lowercase__      :						bool = False    ,					lowercase__      :						bool = True    ,					lowercase__      :						Optional[Union[str, TensorType]] = None    ,					**lowercase__      :						List[str]    ,					):







        '''simple docstring'''



        if self.image_processor.apply_ocr and (boxes is not None):
               raise ValueError(
                   'You cannot provide bounding boxes if you initialized the image processor with apply_ocr set to True.')

        if self.image_processor.apply_ocr and (word_labels is not None):
               raise ValueError(
                   'You cannot provide word labels if you initialized the image processor with apply_ocr set to True.')

        if return_overflowing_tokens is True and return_offsets_mapping is False:
               raise ValueError('You cannot return overflowing tokens without returning the offsets mapping.')

        # first, apply the image processor
        lowerCAmelCase__  			=      self.image_processor(images=lowercase__    ,					return_tensors=lowercase__)

        # second, apply the tokenizer
        if text is not None and self.image_processor.apply_ocr and text_pair is None:
               if isinstance(lowercase__    ,					lowercase__):
                      lowerCAmelCase__  			=      [text]  # add batch dimension (as the image processor always adds a batch dimension)
               lowerCAmelCase__  			=      features['words']

        lowerCAmelCase__  			=      self.tokenizer(
            text=text if text is not None else features['words']    ,					text_pair=text_pair if text_pair is not None else None    ,					boxes=boxes if boxes is not None else features['boxes']    ,					word_labels=lowercase__    ,					add_special_tokens=lowercase__    ,					padding=lowercase__    ,					truncation=lowercase__    ,					max_length=lowercase__    ,					stride=lowercase__    ,					pad_to_multiple_of=lowercase__    ,					return_token_type_ids=lowercase__    ,					return_attention_mask=lowercase__    ,					return_overflowing_tokens=lowercase__    ,					return_special_tokens_mask=lowercase__    ,					return_offsets_mapping=lowercase__    ,					return_length=lowercase__    ,					verbose=lowercase__    ,					return_tensors=lowercase__    ,					**lowercase__    ,					)

        # add pixel values
        lowerCAmelCase__  			=      features.pop('pixel_values')
        if return_overflowing_tokens is True:
               lowerCAmelCase__  			=      self.get_overflowing_images(lowercase__    ,					encoded_inputs['overflow_to_sample_mapping'])
        lowerCAmelCase__  			=      images

        return encoded_inputs




 def 	__snake_case		(    self      :						Optional[int]    ,					lowercase__      :						Optional[Any]    ,					lowercase__      :						Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__  			=      []
        for sample_idx in overflow_to_sample_mapping:
               images_with_overflow.append(images[sample_idx])

        if len(lowercase__) != len(lowercase__):
               raise ValueError(
                   'Expected length of images to be the same as the length of `overflow_to_sample_mapping`, but got'
                   F""" {len(lowercase__)} and {len(lowercase__)}""")

        return images_with_overflow




 def 	__snake_case		(    self      :						List[Any]    ,					*lowercase__      :						Tuple    ,					**lowercase__      :						int):







        '''simple docstring'''



        return self.tokenizer.batch_decode(*lowercase__    ,					**lowercase__)




 def 	__snake_case		(    self      :						List[Any]    ,					*lowercase__      :						str    ,					**lowercase__      :						List[Any]):







        '''simple docstring'''



        return self.tokenizer.decode(*lowercase__    ,					**lowercase__)




 @property
 def 	__snake_case		(    self      :						Tuple):







        '''simple docstring'''



        return ["input_ids", "bbox", "token_type_ids", "attention_mask", "image"]




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







        '''simple docstring'''



        warnings.warn(
            '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'    ,					lowercase__    ,					)
        return self.image_processor_class




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







        '''simple docstring'''



        warnings.warn(
            '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'    ,					lowercase__    ,					)
        return self.image_processor
