


"""simple docstring"""






from __future__ import annotations

import unittest
from collections.abc import Iterator


class      __lowerCamelCase	:

     '''simple docstring'''


     def __init__(   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)							->				None:
          _a     						=					label
          _a     						=					parent
          _a     						=					None
          _a     						=					None







class      __lowerCamelCase	:

     '''simple docstring'''


     def __init__(   self				)							->				None:
          _a     						=					None


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					None


     def 				_UpperCAmelCase   (   self				)							->				bool:
          return self.root is None


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				None:
          _a     						=					self._put(self.root     ,					__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				)							->				Node:
          if node is None:
               _a     						=					Node(__UpperCAmelCase     ,					__UpperCAmelCase				)
          else:
               if label < node.label:
                    _a     						=					self._put(node.left     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)
               elif label > node.label:
                    _a     						=					self._put(node.right     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)
               else:
                    _a     						=					F'Node with label {label} already exists'
                    raise Exception(__UpperCAmelCase				)

          return node


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				Node:
          return self._search(self.root     ,					__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)							->				Node:
          if node is None:
               _a     						=					F'Node with label {label} does not exist'
               raise Exception(__UpperCAmelCase				)
          else:
               if label < node.label:
                    _a     						=					self._search(node.left     ,					__UpperCAmelCase				)
               elif label > node.label:
                    _a     						=					self._search(node.right     ,					__UpperCAmelCase				)

          return node


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				None:
          _a     						=					self.search(__UpperCAmelCase				)
          if node.right and node.left:
               _a     						=					self._get_lowest_node(node.right				)
               _a     						=					node.left
               _a     						=					node.right
               _a     						=					lowest_node
               if node.right:
                    _a     						=					lowest_node
               self._reassign_nodes(__UpperCAmelCase     ,					__UpperCAmelCase				)
          elif not node.right and node.left:
               self._reassign_nodes(__UpperCAmelCase     ,					node.left				)
          elif node.right and not node.left:
               self._reassign_nodes(__UpperCAmelCase     ,					node.right				)
          else:
               self._reassign_nodes(__UpperCAmelCase     ,					__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)							->				None:
          if new_children:
               _a     						=					node.parent

          if node.parent:
               if node.parent.right == node:
                    _a     						=					new_children
               else:
                    _a     						=					new_children
          else:
               _a     						=					new_children


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				Node:
          if node.left:
               _a     						=					self._get_lowest_node(node.left				)
          else:
               _a     						=					node
               self._reassign_nodes(__UpperCAmelCase     ,					node.right				)

          return lowest_node


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				bool:
          try:
               self.search(__UpperCAmelCase				)
               return True
          except Exception:
               return False


     def 				_UpperCAmelCase   (   self				)							->				int:
          if self.root is None:
               raise Exception('''Binary search tree is empty'''				)

          _a     						=					self.root
          while node.right is not None:
               _a     						=					node.right

          return node.label


     def 				_UpperCAmelCase   (   self				)							->				int:
          if self.root is None:
               raise Exception('''Binary search tree is empty'''				)

          _a     						=					self.root
          while node.left is not None:
               _a     						=					node.left

          return node.label


     def 				_UpperCAmelCase   (   self				)							->				Iterator[Node]:
          return self._inorder_traversal(self.root				)


     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				Iterator[Node]:
          if node is not None:
               yield from self._inorder_traversal(node.left				)
               yield node
               yield from self._inorder_traversal(node.right				)


     def 				_UpperCAmelCase   (   self				)							->				Iterator[Node]:
          return self._preorder_traversal(self.root				)





     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase				)							->				Iterator[Node]:
          if node is not None:
               yield node
               yield from self._preorder_traversal(node.left				)
               yield from self._preorder_traversal(node.right				)







class      __lowerCamelCase	(       unittest.TestCase					):

     '''simple docstring'''


     @staticmethod
     def 				_UpperCAmelCase   (   )							->				BinarySearchTree:
          _a     						=					BinarySearchTree()
          t.put(8				)
          t.put(3				)
          t.put(6				)
          t.put(1				)
          t.put(10				)
          t.put(14				)
          t.put(13				)
          t.put(4				)
          t.put(7				)
          t.put(5				)

          return t


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					BinarySearchTree()
          assert t.is_empty()

          t.put(8				)
          assert t.root is not None
          assert t.root.parent is None
          assert t.root.label == 8

          t.put(10				)
          assert t.root.right is not None
          assert t.root.right.parent == t.root
          assert t.root.right.label == 10

          t.put(3				)
          assert t.root.left is not None
          assert t.root.left.parent == t.root
          assert t.root.left.label == 3

          t.put(6				)
          assert t.root.left.right is not None
          assert t.root.left.right.parent == t.root.left
          assert t.root.left.right.label == 6

          t.put(1				)
          assert t.root.left.left is not None
          assert t.root.left.left.parent == t.root.left
          assert t.root.left.left.label == 1

          with self.assertRaises(__UpperCAmelCase				):  # noqa: B017
               t.put(1				)


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          _a     						=					t.search(6				)
          assert node.label == 6

          _a     						=					t.search(13				)
          assert node.label == 13

          with self.assertRaises(__UpperCAmelCase				):  # noqa: B017
               t.search(2				)


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          t.remove(13				)
          assert t.root is not None
          assert t.root.right is not None
          assert t.root.right.right is not None
          assert t.root.right.right.right is None
          assert t.root.right.right.left is None

          t.remove(7				)
          assert t.root.left is not None
          assert t.root.left.right is not None
          assert t.root.left.right.left is not None
          assert t.root.left.right.right is None
          assert t.root.left.right.left.label == 4

          t.remove(6				)
          assert t.root.left.left is not None
          assert t.root.left.right.right is not None
          assert t.root.left.left.label == 1
          assert t.root.left.right.label == 4
          assert t.root.left.right.right.label == 5
          assert t.root.left.right.left is None
          assert t.root.left.left.parent == t.root.left
          assert t.root.left.right.parent == t.root.left

          t.remove(3				)
          assert t.root is not None
          assert t.root.left.label == 4
          assert t.root.left.right.label == 5
          assert t.root.left.left.label == 1
          assert t.root.left.parent == t.root
          assert t.root.left.left.parent == t.root.left
          assert t.root.left.right.parent == t.root.left

          t.remove(4				)
          assert t.root.left is not None
          assert t.root.left.left is not None
          assert t.root.left.label == 5
          assert t.root.left.right is None
          assert t.root.left.left.label == 1
          assert t.root.left.parent == t.root
          assert t.root.left.left.parent == t.root.left


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          t.remove(3				)
          assert t.root is not None
          assert t.root.left is not None
          assert t.root.left.left is not None
          assert t.root.left.right is not None
          assert t.root.left.right.left is not None
          assert t.root.left.right.right is not None
          assert t.root.left.label == 4
          assert t.root.left.right.label == 6
          assert t.root.left.left.label == 1
          assert t.root.left.right.right.label == 7
          assert t.root.left.right.left.label == 5
          assert t.root.left.parent == t.root
          assert t.root.left.right.parent == t.root.left
          assert t.root.left.left.parent == t.root.left
          assert t.root.left.right.left.parent == t.root.left.right


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()
          t.empty()
          assert t.root is None


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()
          assert not t.is_empty()

          t.empty()
          assert t.is_empty()


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          assert t.exists(6				)
          assert not t.exists(-1				)


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          assert t.get_max_label() == 14

          t.empty()
          with self.assertRaises(__UpperCAmelCase				):  # noqa: B017
               t.get_max_label()


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          assert t.get_min_label() == 1

          t.empty()
          with self.assertRaises(__UpperCAmelCase				):  # noqa: B017
               t.get_min_label()


     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          _a     						=					[i.label for i in t.inorder_traversal()]
          assert inorder_traversal_nodes == [1, 3, 4, 5, 6, 7, 8, 10, 13, 14]





     def 				_UpperCAmelCase   (   self				)							->				None:
          _a     						=					self._get_binary_search_tree()

          _a     						=					[i.label for i in t.preorder_traversal()]
          assert preorder_traversal_nodes == [8, 3, 1, 6, 4, 5, 7, 10, 14, 13]







def    A_ ( ):






     """simple docstring"""

     _a     						=					BinarySearchTree()
     t.put(8							)
     t.put(3							)
     t.put(6							)
     t.put(1							)
     t.put(10							)
     t.put(14							)
     t.put(13							)
     t.put(4							)
     t.put(7							)
     t.put(5							)

     print(
         '''
            8
           / \\
          3   10
         / \\    \\
        1   6    14
           / \\   /
          4   7 13
           \\
            5
        '''							)

     print('''Label 6 exists:''',  t.exists(6							)							)
     print('''Label 13 exists:''',  t.exists(13							)							)
     print('''Label -1 exists:''',  t.exists(-1							)							)
     print('''Label 12 exists:''',  t.exists(12							)							)

     # Prints all the elements of the list in inorder traversal
     _a     						=					[i.label for i in t.inorder_traversal()]
     print('''Inorder traversal:''',  _lowerCAmelCase							)

     # Prints all the elements of the list in preorder traversal
     _a     						=					[i.label for i in t.preorder_traversal()]
     print('''Preorder traversal:''',  _lowerCAmelCase							)

     print('''Max. label:''',  t.get_max_label()							)
     print('''Min. label:''',  t.get_min_label()							)

     # Delete elements
     print('''\nDeleting elements 13, 10, 8, 3, 6, 14'''							)
     print(
         '''
          4
         / \\
        1   7
             \\
              5
        '''							)
     t.remove(13							)
     t.remove(10							)
     t.remove(8							)
     t.remove(3							)
     t.remove(6							)
     t.remove(14							)

     # Prints all the elements of the list in inorder traversal after delete
     _a     						=					[i.label for i in t.inorder_traversal()]
     print('''Inorder traversal after delete:''',  _lowerCAmelCase							)

     # Prints all the elements of the list in preorder traversal after delete
     _a     						=					[i.label for i in t.preorder_traversal()]
     print('''Preorder traversal after delete:''',  _lowerCAmelCase							)

     print('''Max. label:''',  t.get_max_label()							)
     print('''Min. label:''',  t.get_min_label()							)


if __name__ == "__main__":
   binary_search_tree_example()



"""simple docstring"""






import torch

from diffusers import DDIMScheduler

from .test_schedulers import SchedulerCommonTest


class      __lowerCamelCase	(       a__					):

     '''simple docstring'''
     A_							:						Tuple     =		(DDIMScheduler,)
     A_							:						Tuple     =		(('eta', 0.0), ('num_inference_steps', 50))


     def 				_UpperCAmelCase   (   self     ,					**__UpperCAmelCase				)							->				str:
          _a     						=					{
              '''num_train_timesteps''': 1000,
              '''beta_start''': 0.0001,
              '''beta_end''': 0.02,
              '''beta_schedule''': '''linear''',
              '''clip_sample''': True,
          }

          config.update(**__UpperCAmelCase				)
          return config


     def 				_UpperCAmelCase   (   self     ,					**__UpperCAmelCase				)							->				List[Any]:
          _a     						=					self.scheduler_classes[0]
          _a     						=					self.get_scheduler_config(**__UpperCAmelCase				)
          _a     						=					scheduler_class(**__UpperCAmelCase				)

          _a						,   _a     						=					10, 0.0

          _a     						=					self.dummy_model()
          _a     						=					self.dummy_sample_deter

          scheduler.set_timesteps(__UpperCAmelCase				)

          for t in scheduler.timesteps:
               _a     						=					model(__UpperCAmelCase     ,					__UpperCAmelCase				)
               _a     						=					scheduler.step(__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				).prev_sample

          return sample


     def 				_UpperCAmelCase   (   self				)							->				str:
          for timesteps in [100, 500, 1000]:
               self.check_over_configs(num_train_timesteps=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				Dict:
          for steps_offset in [0, 1]:
               self.check_over_configs(steps_offset=__UpperCAmelCase				)

          _a     						=					self.scheduler_classes[0]
          _a     						=					self.get_scheduler_config(steps_offset=1				)
          _a     						=					scheduler_class(**__UpperCAmelCase				)
          scheduler.set_timesteps(5				)
          assert torch.equal(scheduler.timesteps     ,					torch.LongTensor([801, 601, 401, 201, 1]				)				)


     def 				_UpperCAmelCase   (   self				)							->				int:
          for beta_start, beta_end in zip([0.0001, 0.001, 0.01, 0.1]     ,					[0.002, 0.02, 0.2, 2]				):
               self.check_over_configs(beta_start=__UpperCAmelCase     ,					beta_end=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				Union[str, Any]:
          for schedule in ["linear", "squaredcos_cap_v2"]:
               self.check_over_configs(beta_schedule=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				List[str]:
          for prediction_type in ["epsilon", "v_prediction"]:
               self.check_over_configs(prediction_type=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				int:
          for clip_sample in [True, False]:
               self.check_over_configs(clip_sample=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				Union[str, Any]:
          for timestep_spacing in ["trailing", "leading"]:
               self.check_over_configs(timestep_spacing=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				List[str]:
          for rescale_betas_zero_snr in [True, False]:
               self.check_over_configs(rescale_betas_zero_snr=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				List[str]:
          self.check_over_configs(thresholding=__UpperCAmelCase				)
          for threshold in [0.5, 1.0, 2.0]:
               for prediction_type in ["epsilon", "v_prediction"]:
                    self.check_over_configs(
                        thresholding=__UpperCAmelCase     ,					prediction_type=__UpperCAmelCase     ,					sample_max_value=__UpperCAmelCase     ,					)


     def 				_UpperCAmelCase   (   self				)							->				int:
          for t in [1, 10, 49]:
               self.check_over_forward(time_step=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				Tuple:
          for t, num_inference_steps in zip([1, 10, 50]     ,					[10, 50, 500]				):
               self.check_over_forward(time_step=__UpperCAmelCase     ,					num_inference_steps=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				Optional[Any]:
          for t, eta in zip([1, 10, 49]     ,					[0.0, 0.5, 1.0]				):
               self.check_over_forward(time_step=__UpperCAmelCase     ,					eta=__UpperCAmelCase				)


     def 				_UpperCAmelCase   (   self				)							->				int:
          _a     						=					self.scheduler_classes[0]
          _a     						=					self.get_scheduler_config()
          _a     						=					scheduler_class(**__UpperCAmelCase				)

          assert torch.sum(torch.abs(scheduler._get_variance(0     ,					0				) - 0.0				)				) < 1e-5
          assert torch.sum(torch.abs(scheduler._get_variance(420     ,					400				) - 0.14771				)				) < 1e-5
          assert torch.sum(torch.abs(scheduler._get_variance(980     ,					960				) - 0.32460				)				) < 1e-5
          assert torch.sum(torch.abs(scheduler._get_variance(0     ,					0				) - 0.0				)				) < 1e-5
          assert torch.sum(torch.abs(scheduler._get_variance(487     ,					486				) - 0.00979				)				) < 1e-5
          assert torch.sum(torch.abs(scheduler._get_variance(999     ,					998				) - 0.02				)				) < 1e-5


     def 				_UpperCAmelCase   (   self				)							->				Optional[int]:
          _a     						=					self.full_loop()

          _a     						=					torch.sum(torch.abs(__UpperCAmelCase				)				)
          _a     						=					torch.mean(torch.abs(__UpperCAmelCase				)				)

          assert abs(result_sum.item() - 172.0067				) < 1e-2
          assert abs(result_mean.item() - 0.223967				) < 1e-3


     def 				_UpperCAmelCase   (   self				)							->				Any:
          _a     						=					self.full_loop(prediction_type='''v_prediction'''				)

          _a     						=					torch.sum(torch.abs(__UpperCAmelCase				)				)
          _a     						=					torch.mean(torch.abs(__UpperCAmelCase				)				)

          assert abs(result_sum.item() - 52.5302				) < 1e-2
          assert abs(result_mean.item() - 0.0684				) < 1e-3


     def 				_UpperCAmelCase   (   self				)							->				List[str]:
          # We specify different beta, so that the first alpha is 0.99
          _a     						=					self.full_loop(set_alpha_to_one=__UpperCAmelCase     ,					beta_start=0.01				)
          _a     						=					torch.sum(torch.abs(__UpperCAmelCase				)				)
          _a     						=					torch.mean(torch.abs(__UpperCAmelCase				)				)

          assert abs(result_sum.item() - 149.8295				) < 1e-2
          assert abs(result_mean.item() - 0.1951				) < 1e-3





     def 				_UpperCAmelCase   (   self				)							->				int:
          # We specify different beta, so that the first alpha is 0.99
          _a     						=					self.full_loop(set_alpha_to_one=__UpperCAmelCase     ,					beta_start=0.01				)
          _a     						=					torch.sum(torch.abs(__UpperCAmelCase				)				)
          _a     						=					torch.mean(torch.abs(__UpperCAmelCase				)				)

          assert abs(result_sum.item() - 149.0784				) < 1e-2
          assert abs(result_mean.item() - 0.1941				) < 1e-3