from __future__ import annotations

from abc import abstractmethod
from collections.abc import Iterable
from typing import Generic, Protocol, TypeVar







class __snake_case							(		lowerCamelCase_						):




   @abstractmethod
   def __lt__(       self     :							T			,      _lowercase     :							T ):



     """simple docstring"""






     pass




   @abstractmethod
   def __gt__(       self     :							T			,      _lowercase     :							T ):



     """simple docstring"""






     pass




   @abstractmethod
   def __eq__(       self     :							T			,      _lowercase     :							object ):



     """simple docstring"""






     pass





__lowerCamelCase     :					Dict				  =						TypeVar('''T''', bound=Comparable)







class __snake_case							(		Generic[T]						):




   def __init__(       self     :							Optional[int] ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= []
     SCREAMING_SNAKE_CASE__     				= 0




   def __repr__(       self     :							Tuple ):



     """simple docstring"""






     return str(self.h )




   def       __a		(       self     :							int			,      _lowercase     :							int ):



     """simple docstring"""






     if child_idx > 0:
       return (child_idx - 1) // 2
     return None




   def       __a		(       self     :							List[str]			,      _lowercase     :							int ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= 2 * parent_idx + 1
     if left_child_index < self.heap_size:
       return left_child_index
     return None




   def       __a		(       self     :							Tuple			,      _lowercase     :							int ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= 2 * parent_idx + 2
     if right_child_index < self.heap_size:
       return right_child_index
     return None




   def       __a		(       self     :							Tuple			,      _lowercase     :							int ):



     """simple docstring"""






     if index < self.heap_size:
       SCREAMING_SNAKE_CASE__     				= index
       SCREAMING_SNAKE_CASE__     				= self.left_child_idx(_lowercase )
       SCREAMING_SNAKE_CASE__     				= self.right_child_idx(_lowercase )
       # check which child is larger than its parent
       if left_child is not None and self.h[left_child] > self.h[violation]:
         SCREAMING_SNAKE_CASE__     				= left_child
       if right_child is not None and self.h[right_child] > self.h[violation]:
         SCREAMING_SNAKE_CASE__     				= right_child
       # if violation indeed exists
       if violation != index:
         # swap to fix the violation
         SCREAMING_SNAKE_CASE__				,	SCREAMING_SNAKE_CASE__     				= self.h[index], self.h[violation]
         # fix the subsequent violation recursively if any
         self.max_heapify(_lowercase )




   def       __a		(       self     :							Optional[Any]			,      _lowercase     :							Iterable[T] ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= list(_lowercase )
     SCREAMING_SNAKE_CASE__     				= len(self.h )
     if self.heap_size > 1:
       # max_heapify from right to left but exclude leaves (last level)
       for i in range(self.heap_size // 2 - 1			,      -1			,      -1 ):
         self.max_heapify(_lowercase )




   def       __a		(       self     :							Optional[Any] ):



     """simple docstring"""






     if self.heap_size >= 2:
       SCREAMING_SNAKE_CASE__     				= self.h[0]
       SCREAMING_SNAKE_CASE__     				= self.h.pop(-1 )
       self.heap_size -= 1
       self.max_heapify(0 )
       return me
     elif self.heap_size == 1:
       self.heap_size -= 1
       return self.h.pop(-1 )
     else:
       raise Exception("""Empty heap""" )




   def       __a		(       self     :							Optional[int]			,      _lowercase     :							T ):



     """simple docstring"""






     self.h.append(_lowercase )
     SCREAMING_SNAKE_CASE__     				= (self.heap_size - 1) // 2
     self.heap_size += 1
     while idx >= 0:
       self.max_heapify(_lowercase )
       SCREAMING_SNAKE_CASE__     				= (idx - 1) // 2




   def       __a		(       self     :							Tuple ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= self.heap_size
     for j in range(size - 1			,      0			,      -1 ):
       SCREAMING_SNAKE_CASE__				,	SCREAMING_SNAKE_CASE__     				= self.h[j], self.h[0]
       self.heap_size -= 1
       self.max_heapify(0 )
     SCREAMING_SNAKE_CASE__     				= size


if __name__ == "__main__":
   import doctest

   # run doc test
   doctest.testmod()

   # demo
   for unsorted in [
       [0],
       [2],
       [3, 5],
       [5, 3],
       [5, 5],
       [0, 0, 0, 0],
       [1, 1, 1, 1],
       [2, 2, 3, 5],
       [0, 2, 2, 3, 5],
       [2, 5, 3, 0, 2, 3, 0, 3],
       [6, 1, 2, 7, 9, 3, 4, 5, 10, 8],
       [103, 9, 1, 7, 11, 15, 25, 201, 209, 107, 5],
       [-45, -2, -5],
   ]:
      print(F"""unsorted array: {unsorted}""")

      __lowerCamelCase     :					Heap[int]				  =						Heap()
      heap.build_max_heap(unsorted)
      print(F"""after build heap: {heap}""")

      print(F"""max value: {heap.extract_max()}""")
      print(F"""after max value removed: {heap}""")

      heap.insert(100)
      print(F"""after new value 100 inserted: {heap}""")

      heap.heap_sort()
      print(F"""heap-sorted array: {heap}\n""")

import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference







@slow
@require_torch_gpu
class __snake_case							(		unittest.TestCase						):




   def       __a		(       self     :							List[Any] ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__     				= """runwayml/stable-diffusion-v1-5"""
     SCREAMING_SNAKE_CASE__     				= TextToVideoZeroPipeline.from_pretrained(_lowercase			,      torch_dtype=torch.floataa ).to("""cuda""" )
     SCREAMING_SNAKE_CASE__     				= DDIMScheduler.from_config(pipe.scheduler.config )
     SCREAMING_SNAKE_CASE__     				= torch.Generator(device="""cuda""" ).manual_seed(0 )

     SCREAMING_SNAKE_CASE__     				= """A bear is playing a guitar on Times Square"""
     SCREAMING_SNAKE_CASE__     				= pipe(prompt=_lowercase			,      generator=_lowercase ).images

     SCREAMING_SNAKE_CASE__     				= load_pt(
         """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt""" )

     assert_mean_pixel_difference(_lowercase			,      _lowercase )
