






"""simple docstring"""



class 			a	:







    def __init__(     self				,						_lowerCamelCase			):
      lowercase				       =			val
      # Number of nodes in left subtree
      lowercase				       =			0
      lowercase				       =			None
      lowercase				       =			None
      lowercase				       =			None







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

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


class 			a	:







    def __init__(     self				,						_lowerCamelCase=None				,						_lowerCamelCase=None				,						_lowerCamelCase=0			):
      lowercase				       =			heap_size
      lowercase				       =			bottom_root
      lowercase				       =			min_node







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):

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

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

      # Order roots by left_subtree_size
      lowercase				       =			[]
      lowercase       ,	lowercase				       =			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)			)
          lowercase				       =			i.parent
        else:
          combined_roots_list.append((j, False)			)
          lowercase				       =			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]:
          lowercase				       =			combined_roots_list[i + 1][0]
          lowercase				       =			combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
      lowercase				       =			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
          lowercase				       =			i.left
          lowercase				       =			i.parent.parent

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

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

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

      # Return the merged heap
      return self







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):

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

        # Update size
        self.size += 1

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

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

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







    def      UpperCamelCase_ (     self			):
      return self.min_node.val







    def      UpperCamelCase_ (     self			):
      return self.size == 0







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.min_node.val

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

        # Update bottom root
        lowercase				       =			None

        # Update min_node
        lowercase				       =			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
        lowercase				       =			self.bottom_root.parent
        lowercase				       =			None

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

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

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

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

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

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

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

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

      return min_value







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.bottom_root
      while top_root.parent:
        lowercase				       =			top_root.parent
      # preorder
      lowercase				       =			[]
      self.__traversal(_lowerCamelCase				,						_lowerCamelCase			)
      return heap_pre_order







    def      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase				,						_lowerCamelCase=0			):

      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			):

      if self.is_empty():
        return ""
      lowercase				       =			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 shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
       from PIL import Image

       from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast

@require_vision
class 			__A(    unittest.TestCase			):

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    tempfile.mkdtemp()

            _UpperCamelCase														=    CLIPImageProcessor()
            _UpperCamelCase														=    BertTokenizer.from_pretrained(
                '''hf-internal-testing/tiny-random-BertModel''',							model_input_names=['''input_ids''', '''attention_mask''']   )

            _UpperCamelCase														=    GitProcessor(A,							A   )

            processor.save_pretrained(self.tmpdirname   )

     def 						_UpperCamelCase  (   self,							**A   ):





            """simple docstring"""

            return AutoProcessor.from_pretrained(self.tmpdirname,							**A   ).tokenizer

     def 						_UpperCamelCase  (   self,							**A   ):





            """simple docstring"""

            return AutoProcessor.from_pretrained(self.tmpdirname,							**A   ).image_processor

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            shutil.rmtree(self.tmpdirname   )

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    [np.random.randint(255,							size=(3, 30, 400),							dtype=np.uinta   )]

            _UpperCamelCase														=    [Image.fromarray(np.moveaxis(A,							0,							-1   )   ) for x in image_inputs]

            return image_inputs

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    GitProcessor(tokenizer=self.get_tokenizer(),							image_processor=self.get_image_processor()   )
            processor.save_pretrained(self.tmpdirname   )

            _UpperCamelCase														=    self.get_tokenizer(bos_token='''(BOS)''',							eos_token='''(EOS)'''   )
            _UpperCamelCase														=    self.get_image_processor(do_normalize=A,							padding_value=1.0   )

            _UpperCamelCase														=    GitProcessor.from_pretrained(
                self.tmpdirname,							bos_token='''(BOS)''',							eos_token='''(EOS)''',							do_normalize=A,							padding_value=1.0   )

            self.assertEqual(processor.tokenizer.get_vocab(),							tokenizer_add_kwargs.get_vocab()   )
            self.assertIsInstance(processor.tokenizer,							A   )

            self.assertEqual(processor.image_processor.to_json_string(),							image_processor_add_kwargs.to_json_string()   )
            self.assertIsInstance(processor.image_processor,							A   )

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    self.get_image_processor()
            _UpperCamelCase														=    self.get_tokenizer()

            _UpperCamelCase														=    GitProcessor(tokenizer=A,							image_processor=A   )

            _UpperCamelCase														=    self.prepare_image_inputs()

            _UpperCamelCase														=    image_processor(A,							return_tensors='''np'''   )
            _UpperCamelCase														=    processor(images=A,							return_tensors='''np'''   )

            for key in input_feat_extract.keys():
                   self.assertAlmostEqual(input_feat_extract[key].sum(),							input_processor[key].sum(),							delta=1E-2   )

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    self.get_image_processor()
            _UpperCamelCase														=    self.get_tokenizer()

            _UpperCamelCase														=    GitProcessor(tokenizer=A,							image_processor=A   )

            _UpperCamelCase														=    '''lower newer'''

            _UpperCamelCase														=    processor(text=A   )

            _UpperCamelCase														=    tokenizer(A,							return_token_type_ids=A   )

            for key in encoded_tok.keys():
                   self.assertListEqual(encoded_tok[key],							encoded_processor[key]   )

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    self.get_image_processor()
            _UpperCamelCase														=    self.get_tokenizer()

            _UpperCamelCase														=    GitProcessor(tokenizer=A,							image_processor=A   )

            _UpperCamelCase														=    '''lower newer'''
            _UpperCamelCase														=    self.prepare_image_inputs()

            _UpperCamelCase														=    processor(text=A,							images=A   )

            self.assertListEqual(list(inputs.keys()   ),							['''input_ids''', '''attention_mask''', '''pixel_values''']   )

            # test if it raises when no input is passed
            with pytest.raises(A   ):
                   processor()

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    self.get_image_processor()
            _UpperCamelCase														=    self.get_tokenizer()

            _UpperCamelCase														=    GitProcessor(tokenizer=A,							image_processor=A   )

            _UpperCamelCase														=    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            _UpperCamelCase														=    processor.batch_decode(A   )
            _UpperCamelCase														=    tokenizer.batch_decode(A   )

            self.assertListEqual(A,							A   )



     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    self.get_image_processor()
            _UpperCamelCase														=    self.get_tokenizer()

            _UpperCamelCase														=    GitProcessor(tokenizer=A,							image_processor=A   )

            _UpperCamelCase														=    '''lower newer'''
            _UpperCamelCase														=    self.prepare_image_inputs()

            _UpperCamelCase														=    processor(text=A,							images=A   )

            # For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
            self.assertListEqual(list(inputs.keys()   ),							['''input_ids''', '''attention_mask''', '''pixel_values''']   )






