"""simple docstring"""







from collections.abc import Iterable
from typing import Any

class 		UpperCamelCase      :






				"""simple docstring"""




				def __init__(self    :				Optional[int]     ,  _A    :				str = None)   ->     int:
					__snake_case      :							int						=			value
					__snake_case      :							List[str]						=			None  # Added in order to delete a node easier
					__snake_case      :							int						=			None
					__snake_case      :							Union[str, Any]						=			None






				def __repr__(self    :				List[Any])   ->     str:
					from pprint import pformat

					if self.left is None and self.right is None:
						return str(self.value)
					return pformat({f"{self.value}": (self.left, self.right)}     ,  indent=1)







class 		UpperCamelCase      :






				"""simple docstring"""




				def __init__(self    :				Tuple     ,  _A    :				Optional[Any] = None)   ->     Tuple:
					__snake_case      :							Dict						=			root



				def __str__(self    :				Optional[int])   ->     str:
					return str(self.root)



				def  _lowercase					(self    :				Any     ,  _A    :				Union[str, Any]     ,  _A    :				Tuple)   ->     None:
					if new_children is not None:  # reset its kids
						__snake_case      :							int						=			node.parent
					if node.parent is not None:  # reset its parent
						if self.is_right(_A):  # If it is the right children
							__snake_case      :							Dict						=			new_children
						else:
							__snake_case      :							List[Any]						=			new_children
					else:
						__snake_case      :							Union[str, Any]						=			new_children



				def  _lowercase					(self    :				Dict     ,  _A    :				List[str])   ->     bool:
					if node.parent and node.parent.right:
						return node == node.parent.right
					return False



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



				def  _lowercase					(self    :				Tuple     ,  _A    :				Optional[int])   ->     None:
					__snake_case      :							List[str]						=			Node(_A)  # create a new Node
					if self.empty():  # if Tree is empty
						__snake_case      :							str						=			new_node  # set its root
					else:  # Tree is not empty
						__snake_case      :							List[str]						=			self.root  # from root
						if parent_node is None:
							return
						while True:  # While we don't get to a leaf
							if value < parent_node.value:  # We go left
								if parent_node.left is None:
									__snake_case      :							Tuple						=			new_node  # We insert the new node in a leaf
									break
								else:
									__snake_case      :							Union[str, Any]						=			parent_node.left
							else:
								if parent_node.right is None:
									__snake_case      :							Union[str, Any]						=			new_node
									break
								else:
									__snake_case      :							Union[str, Any]						=			parent_node.right
						__snake_case      :							Optional[Any]						=			parent_node



				def  _lowercase					(self    :				Any     ,  *_A    :				List[Any])   ->     None:
					for value in values:
						self.__insert(_A)



				def  _lowercase					(self    :				Any     ,  _A    :				List[Any])   ->     Node | None:
					if self.empty():
						raise IndexError('Warning: Tree is empty! please use another.')
					else:
						__snake_case      :							Optional[Any]						=			self.root
						# use lazy evaluation here to avoid NoneType Attribute error
						while node is not None and node.value is not value:
							__snake_case      :							str						=			node.left if value < node.value else node.right
						return node



				def  _lowercase					(self    :				List[Any]     ,  _A    :				Optional[Any] = None)   ->     Node | None:
					if node is None:
						if self.root is None:
							return None
						__snake_case      :							List[str]						=			self.root

					if not self.empty():
						while node.right is not None:
							__snake_case      :							int						=			node.right
					return node



				def  _lowercase					(self    :				Any     ,  _A    :				Union[str, Any] = None)   ->     Node | None:
					if node is None:
						__snake_case      :							List[str]						=			self.root
					if self.root is None:
						return None
					if not self.empty():
						__snake_case      :							int						=			self.root
						while node.left is not None:
							__snake_case      :							int						=			node.left
					return node



				def  _lowercase					(self    :				List[Any]     ,  _A    :				Union[str, Any])   ->     None:
					__snake_case      :							Tuple						=			self.search(_A)  # Look for the node with that label
					if node is not None:
						if node.left is None and node.right is None:  # If it has no children
							self.__reassign_nodes(_A     ,  _A)
						elif node.left is None:  # Has only right children
							self.__reassign_nodes(_A     ,  node.right)
						elif node.right is None:  # Has only left children
							self.__reassign_nodes(_A     ,  node.left)
						else:
							__snake_case      :							Optional[int]						=			self.get_max(
							    node.left)  # Gets the max value of the left branch
							self.remove(tmp_node.value)  # type: ignore
							__snake_case      :							Union[str, Any]						=			(
							    tmp_node.value  # type: ignore
							)  # Assigns the value to the node to delete and keep tree structure



				def  _lowercase					(self    :				List[str]     ,  _A    :				Optional[Any])   ->     Iterable:
					if node is not None:
						yield node  # Preorder Traversal
						yield from self.preorder_traverse(node.left)
						yield from self.preorder_traverse(node.right)



				def  _lowercase					(self    :				Any     ,  _A    :				int=None)   ->     Any:
					if traversal_function is None:
						return self.preorder_traverse(self.root)
					else:
						return traversal_function(self.root)



				def  _lowercase					(self    :				int     ,  _A    :				str     ,  _A    :				Tuple)   ->     None:
					if node:
						self.inorder(_A     ,  node.left)
						arr.append(node.value)
						self.inorder(_A     ,  node.right)






				def  _lowercase					(self    :				str     ,  _A    :				Optional[Any]     ,  _A    :				Any)   ->     int:
					__snake_case      :							Any						=			[]
					self.inorder(_A     ,  _A)  # append all values to list using inorder traversal
					return arr[k - 1]







def   __UpperCAmelCase    (   UpperCAmelCase_   :    Node | None  )							->      list[Node]:

	'''simple docstring'''





	__snake_case      :							Any						=			[]
	if curr_node is not None:
		__snake_case      :							Optional[int]						=			postorder(curr_node.left  ) + postorder(curr_node.right  ) + [curr_node]
	return node_list
def   __UpperCAmelCase    (   )							->      None:

	'''simple docstring'''





	__snake_case      :							List[str]						=			(8, 3, 6, 1, 10, 14, 13, 4, 7)
	__snake_case      :							Dict						=			BinarySearchTree()
	for i in testlist:
		t.insert(lowerCAmelCase__  )

	# Prints all the elements of the list in order traversal
	print(lowerCAmelCase__  )

	if t.search(6  ) is not None:
		print('The value 6 exists'  )
	else:
		print('The value 6 doesn\'t exist'  )

	if t.search(-1  ) is not None:
		print('The value -1 exists'  )
	else:
		print('The value -1 doesn\'t exist'  )

	if not t.empty():
		print('Max Value: '      ,							t.get_max().value  )  # type: ignore
		print('Min Value: '      ,							t.get_min().value  )  # type: ignore

	for i in testlist:
		t.remove(lowerCAmelCase__  )
		print(lowerCAmelCase__  )


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)






"""simple docstring"""







import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / "utils"))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402

class 		UpperCamelCase      (   unittest.TestCase						):



				def  _lowercase					(self    :				Union[str, Any])   ->     Optional[int]:
					__snake_case      :							Optional[Any]						=			0



				def  _lowercase					(self    :				Tuple)   ->     int:
					__snake_case      :							Optional[Any]						=			AutoImageProcessor.from_pretrained('openai/clip-vit-base-patch32')
					self.assertIsInstance(_A     ,  _A)



				def  _lowercase					(self    :				str)   ->     List[str]:
					with tempfile.TemporaryDirectory() as tmpdirname:
						__snake_case      :							List[str]						=			Path(_A) / 'preprocessor_config.json'
						__snake_case      :							Optional[Any]						=			Path(_A) / 'config.json'
						json.dump(
						    {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}     ,  open(_A     ,  'w')     ,  )
						json.dump({'model_type': 'clip'}     ,  open(_A     ,  'w'))

						__snake_case      :							Optional[int]						=			AutoImageProcessor.from_pretrained(_A)
						self.assertIsInstance(_A     ,  _A)



				def  _lowercase					(self    :				Any)   ->     Optional[int]:
					# Ensure we can load the image processor from the feature extractor config
					with tempfile.TemporaryDirectory() as tmpdirname:
						__snake_case      :							Any						=			Path(_A) / 'preprocessor_config.json'
						__snake_case      :							List[Any]						=			Path(_A) / 'config.json'
						json.dump(
						    {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}     ,  open(_A     ,  'w')     ,  )
						json.dump({'model_type': 'clip'}     ,  open(_A     ,  'w'))

						__snake_case      :							Tuple						=			AutoImageProcessor.from_pretrained(_A)
						self.assertIsInstance(_A     ,  _A)



				def  _lowercase					(self    :				List[Any])   ->     Optional[Any]:
					with tempfile.TemporaryDirectory() as tmpdirname:
						__snake_case      :							str						=			CLIPConfig()

						# Create a dummy config file with image_proceesor_type
						__snake_case      :							List[Any]						=			Path(_A) / 'preprocessor_config.json'
						__snake_case      :							Optional[Any]						=			Path(_A) / 'config.json'
						json.dump(
						    {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}     ,  open(_A     ,  'w')     ,  )
						json.dump({'model_type': 'clip'}     ,  open(_A     ,  'w'))

						# remove image_processor_type to make sure config.json alone is enough to load image processor locally
						__snake_case      :							List[str]						=			AutoImageProcessor.from_pretrained(_A).to_dict()

						config_dict.pop('image_processor_type')
						__snake_case      :							Optional[int]						=			CLIPImageProcessor(**_A)

						# save in new folder
						model_config.save_pretrained(_A)
						config.save_pretrained(_A)

						__snake_case      :							Optional[int]						=			AutoImageProcessor.from_pretrained(_A)

						# make sure private variable is not incorrectly saved
						__snake_case      :							int						=			json.loads(config.to_json_string())
						self.assertTrue('_processor_class' not in dict_as_saved)

					self.assertIsInstance(_A     ,  _A)



				def  _lowercase					(self    :				Union[str, Any])   ->     Optional[Any]:
					with tempfile.TemporaryDirectory() as tmpdirname:
						__snake_case      :							int						=			Path(_A) / 'preprocessor_config.json'
						json.dump(
						    {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}     ,  open(_A     ,  'w')     ,  )

						__snake_case      :							List[str]						=			AutoImageProcessor.from_pretrained(_A)
						self.assertIsInstance(_A     ,  _A)



				def  _lowercase					(self    :				Optional[int])   ->     Dict:
					with self.assertRaisesRegex(
					    _A     ,  'clip-base is not a local folder and is not a valid model identifier'):
						__snake_case      :							Tuple						=			AutoImageProcessor.from_pretrained('clip-base')



				def  _lowercase					(self    :				str)   ->     int:
					with self.assertRaisesRegex(
					    _A     ,  r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'):
						__snake_case      :							str						=			AutoImageProcessor.from_pretrained(_A     ,  revision='aaaaaa')



				def  _lowercase					(self    :				List[Any])   ->     str:
					with self.assertRaisesRegex(
					    _A     ,  'hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'     ,  ):
						__snake_case      :							List[Any]						=			AutoImageProcessor.from_pretrained('hf-internal-testing/config-no-model')



				def  _lowercase					(self    :				Optional[int])   ->     List[str]:
					# If remote code is not set, we will time out when asking whether to load the model.
					with self.assertRaises(_A):
						__snake_case      :							Any						=			AutoImageProcessor.from_pretrained('hf-internal-testing/test_dynamic_image_processor')
					# If remote code is disabled, we can't load this config.
					with self.assertRaises(_A):
						__snake_case      :							Tuple						=			AutoImageProcessor.from_pretrained(
						    'hf-internal-testing/test_dynamic_image_processor'     ,  trust_remote_code=_A)

					__snake_case      :							Union[str, Any]						=			AutoImageProcessor.from_pretrained(
					    'hf-internal-testing/test_dynamic_image_processor'     ,  trust_remote_code=_A)
					self.assertEqual(image_processor.__class__.__name__     ,  'NewImageProcessor')

					# Test image processor can be reloaded.
					with tempfile.TemporaryDirectory() as tmp_dir:
						image_processor.save_pretrained(_A)
						__snake_case      :							Optional[int]						=			AutoImageProcessor.from_pretrained(_A     ,  trust_remote_code=_A)
					self.assertEqual(reloaded_image_processor.__class__.__name__     ,  'NewImageProcessor')



				def  _lowercase					(self    :				int)   ->     Optional[int]:
					try:
						AutoConfig.register('custom'     ,  _A)
						AutoImageProcessor.register(_A     ,  _A)
						# Trying to register something existing in the Transformers library will raise an error
						with self.assertRaises(_A):
							AutoImageProcessor.register(_A     ,  _A)

						with tempfile.TemporaryDirectory() as tmpdirname:
							__snake_case      :							Tuple						=			Path(_A) / 'preprocessor_config.json'
							__snake_case      :							Dict						=			Path(_A) / 'config.json'
							json.dump(
							    {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}     ,  open(_A     ,  'w')     ,  )
							json.dump({'model_type': 'clip'}     ,  open(_A     ,  'w'))

							__snake_case      :							Tuple						=			CustomImageProcessor.from_pretrained(_A)

						# Now that the config is registered, it can be used as any other config with the auto-API
						with tempfile.TemporaryDirectory() as tmp_dir:
							image_processor.save_pretrained(_A)
							__snake_case      :							Tuple						=			AutoImageProcessor.from_pretrained(_A)
							self.assertIsInstance(_A     ,  _A)

					finally:
						if "custom" in CONFIG_MAPPING._extra_content:
							del CONFIG_MAPPING._extra_content["custom"]
						if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
							del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]






				def  _lowercase					(self    :				List[Any])   ->     Tuple:

					class 		UpperCamelCase      (   lowercase						):
									UpperCAmelCase    :				str   =		True

					try:
						AutoConfig.register('custom'     ,  _A)
						AutoImageProcessor.register(_A     ,  _A)
						# If remote code is not set, the default is to use local
						__snake_case      :							Tuple						=			AutoImageProcessor.from_pretrained('hf-internal-testing/test_dynamic_image_processor')
						self.assertEqual(image_processor.__class__.__name__     ,  'NewImageProcessor')
						self.assertTrue(image_processor.is_local)

						# If remote code is disabled, we load the local one.
						__snake_case      :							Optional[int]						=			AutoImageProcessor.from_pretrained(
						    'hf-internal-testing/test_dynamic_image_processor'     ,  trust_remote_code=_A)
						self.assertEqual(image_processor.__class__.__name__     ,  'NewImageProcessor')
						self.assertTrue(image_processor.is_local)

						# If remote is enabled, we load from the Hub
						__snake_case      :							List[Any]						=			AutoImageProcessor.from_pretrained(
						    'hf-internal-testing/test_dynamic_image_processor'     ,  trust_remote_code=_A)
						self.assertEqual(image_processor.__class__.__name__     ,  'NewImageProcessor')
						self.assertTrue(not hasattr(_A     ,  'is_local'))

					finally:
						if "custom" in CONFIG_MAPPING._extra_content:
							del CONFIG_MAPPING._extra_content["custom"]
						if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
							del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]





