class 			__snake_case   :
 def __init__(  self		,   snake_case__						)	->							str:
       '''simple docstring'''





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






 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							Union[str, Any]:
       '''simple docstring'''





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

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







class 			__snake_case   :
 def __init__(  self		,   snake_case__=None		,   snake_case__=None		,   snake_case__=0						)	->							List[str]:
       '''simple docstring'''





       UpperCAmelCase    : Dict      =heap_size
       UpperCAmelCase    : Union[str, Any]      =bottom_root
       UpperCAmelCase    : Tuple      =min_node
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							str:
       '''simple docstring'''





       if other.size == 0:
             return None
       if self.size == 0:
             UpperCAmelCase    : Tuple      =other.size
             UpperCAmelCase    : Dict      =other.bottom_root
             UpperCAmelCase    : Tuple      =other.min_node
             return None
       # Update size
       UpperCAmelCase    : Tuple      =self.size + other.size

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

       # Order roots by left_subtree_size
       UpperCAmelCase    : Optional[Any]      =[]
       UpperCAmelCase  ,						UpperCAmelCase    : Tuple      =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)						)
                   UpperCAmelCase    : Tuple      =i.parent
             else:
                   combined_roots_list.append((j, False)						)
                   UpperCAmelCase    : Tuple      =j.parent
        # Insert links between them
       for i in range(len(snake_case__						) - 1						):
             if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
                   UpperCAmelCase    : Union[str, Any]      =combined_roots_list[i + 1][0]
                   UpperCAmelCase    : Optional[int]      =combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
       UpperCAmelCase    : int      =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
                   UpperCAmelCase    : int      =i.left
                   UpperCAmelCase    : int      =i.parent.parent

                   # Merging trees
                   UpperCAmelCase    : List[str]      =i.merge_trees(i.parent						)

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

       # Update other
       UpperCAmelCase    : Any      =self.size
       UpperCAmelCase    : str      =self.bottom_root
       UpperCAmelCase    : int      =self.min_node

       # Return the merged heap
       return self
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							Any:
       '''simple docstring'''





       if self.size == 0:
             UpperCAmelCase    : int      =Node(snake_case__						)
             UpperCAmelCase    : int      =1
             UpperCAmelCase    : int      =self.bottom_root
       else:
             # Create new node
             UpperCAmelCase    : int      =Node(snake_case__						)

             # Update size
             self.size += 1

             # update min_node
             if val < self.min_node.val:
                   UpperCAmelCase    : Optional[int]      =new_node
             # Put new_node as a bottom_root in heap
             UpperCAmelCase    : Optional[int]      =new_node
             UpperCAmelCase    : Any      =self.bottom_root
             UpperCAmelCase    : List[str]      =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
                   UpperCAmelCase    : Union[str, Any]      =self.bottom_root.parent.parent

                   # Merge
                   UpperCAmelCase    : Any      =self.bottom_root.merge_trees(self.bottom_root.parent						)

                   # Update Links
                   UpperCAmelCase    : Any      =next_node
                   UpperCAmelCase    : str      =None
                   if next_node:
                         UpperCAmelCase    : Tuple      =self.bottom_root
 def 	UpperCAmelCase__       (  self						)	->							int:
       '''simple docstring'''





       return self.min_node.val
 def 	UpperCAmelCase__       (  self						)	->							List[str]:
       '''simple docstring'''





       return self.size == 0
 def 	UpperCAmelCase__       (  self						)	->							Any:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =self.min_node.val

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

             # Update bottom root
             UpperCAmelCase    : Optional[Any]      =None

             # Update min_node
             UpperCAmelCase    : Tuple      =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
             UpperCAmelCase    : List[Any]      =self.bottom_root.parent
             UpperCAmelCase    : List[Any]      =None

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

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

       # Update size
       UpperCAmelCase    : Optional[Any]      =self.size - 1 - size_of_new

       # Neighbour nodes
       UpperCAmelCase    : Optional[Any]      =self.min_node.left
       UpperCAmelCase    : List[Any]      =self.min_node.parent

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

       # Update links of previous_node and search below for new min_node and
       # bottom_root
       if previous_node:
             UpperCAmelCase    : Union[str, Any]      =next_node

             # Update bottom_root and search for min_node below
             UpperCAmelCase    : List[Any]      =previous_node
             UpperCAmelCase    : Optional[Any]      =previous_node
             while self.bottom_root.left:
                   UpperCAmelCase    : List[Any]      =self.bottom_root.left
                   if self.bottom_root.val < self.min_node.val:
                         UpperCAmelCase    : List[Any]      =self.bottom_root
       if next_node:
             UpperCAmelCase    : Union[str, Any]      =previous_node

             # Search for new min_node above min_node
             UpperCAmelCase    : str      =next_node
             while i:
                   if i.val < self.min_node.val:
                         UpperCAmelCase    : Any      =i
                   UpperCAmelCase    : Any      =i.parent
        # Merge heaps
       self.merge_heaps(snake_case__						)

       return min_value
 def 	UpperCAmelCase__       (  self						)	->							Any:
       '''simple docstring'''





       UpperCAmelCase    : Union[str, Any]      =self.bottom_root
       while top_root.parent:
             UpperCAmelCase    : Tuple      =top_root.parent
       # preorder
       UpperCAmelCase    : Optional[int]      =[]
       self.__traversal(snake_case__		,   snake_case__						)
       return heap_pre_order
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__		,   snake_case__=0						)	->							Optional[Any]:
       '''simple docstring'''





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






 def __str__(  self						)	->							Dict:
       '''simple docstring'''





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

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


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

     doctest.testmod()

import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard







class 			__snake_case   (     unittest.TestCase   ):
 def 	UpperCAmelCase__       (  self						)	->							Optional[Any]:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      ={
           '''model_details''': {
               '''Organization''': '''testing''',
               '''Model date''': '''today''',
               '''Model version''': '''v2.1, Developed by Test Corp in 2019.''',
               '''Architecture''': '''Convolutional Neural Network.''',
           },
           '''metrics''': '''BLEU and ROUGE-1''',
           '''evaluation_data''': {
               '''Datasets''': {'''BLEU''': '''My-great-dataset-v1''', '''ROUGE-1''': '''My-short-dataset-v2.1'''},
               '''Preprocessing''': '''See details on https://arxiv.org/pdf/1810.03993.pdf''',
           },
           '''training_data''': {
               '''Dataset''': '''English Wikipedia dump dated 2018-12-01''',
               '''Preprocessing''': (
                   '''Using SentencePiece vocabulary of size 52k tokens. See details on'''
                   ''' https://arxiv.org/pdf/1810.03993.pdf'''
               ),
           },
           '''quantitative_analyses''': {'''BLEU''': 55.1, '''ROUGE-1''': 76},
       }
 def 	UpperCAmelCase__       (  self						)	->							Dict:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =ModelCard.from_dict(self.inputs_dict						)
       self.assertTrue(hasattr(snake_case__		,   '''model_details'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''intended_use'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''factors'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''metrics'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''evaluation_data'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''training_data'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''quantitative_analyses'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''ethical_considerations'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''caveats_and_recommendations'''						)						)
 def 	UpperCAmelCase__       (  self						)	->							Tuple:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =ModelCard.from_dict(self.inputs_dict						)
       UpperCAmelCase    : int      =json.loads(modelcard.to_json_string()						)
       for key, value in self.inputs_dict.items():
             self.assertEqual(obj[key]		,   snake_case__						)
 def 	UpperCAmelCase__       (  self						)	->							Tuple:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =ModelCard.from_dict(self.inputs_dict						)

       with tempfile.TemporaryDirectory() as tmpdirname:
             UpperCAmelCase    : Optional[Any]      =os.path.join(snake_case__		,   '''modelcard.json'''						)
             model_card_first.to_json_file(snake_case__						)
             UpperCAmelCase    : Tuple      =ModelCard.from_json_file(snake_case__						)

       self.assertEqual(model_card_second.to_dict()		,   model_card_first.to_dict()						)






 def 	UpperCAmelCase__       (  self						)	->							str:
       '''simple docstring'''





       UpperCAmelCase    : Optional[int]      =ModelCard.from_dict(self.inputs_dict						)

       with tempfile.TemporaryDirectory() as tmpdirname:
             model_card_first.save_pretrained(snake_case__						)
             UpperCAmelCase    : Dict      =ModelCard.from_pretrained(snake_case__						)

       self.assertEqual(model_card_second.to_dict()		,   model_card_first.to_dict()						)
