





"""simple docstring"""
from __future__ import annotations

import unittest
from collections.abc import Iterator






class    _UpperCAmelCase  :


					def __init__(   self     :int	,			__UpperCamelCase     :int	,			__UpperCamelCase     :Node | None						):
												A						=    label
												A						=    parent
												A						=    None
												A						=    None







class    _UpperCAmelCase  :


					def __init__(   self     :List[str]						):
												A						=    None


					def       lowerCamelCase			(   self     :Union[str, Any]						):
												A						=    None


					def       lowerCamelCase			(   self     :Dict						):
												return self.root is None


					def       lowerCamelCase			(   self     :Dict	,			__UpperCamelCase     :int						):
												A						=    self._put(self.root	,			__UpperCamelCase						)


					def       lowerCamelCase			(   self     :str	,			__UpperCamelCase     :Node | None	,			__UpperCamelCase     :int	,			__UpperCamelCase     :Node | None = None						):
												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       lowerCamelCase			(   self     :int	,			__UpperCamelCase     :int						):
												return self._search(self.root	,			__UpperCamelCase						)


					def       lowerCamelCase			(   self     :Optional[Any]	,			__UpperCamelCase     :Node | None	,			__UpperCamelCase     :int						):
												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       lowerCamelCase			(   self     :Union[str, Any]	,			__UpperCamelCase     :int						):
												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       lowerCamelCase			(   self     :Optional[int]	,			__UpperCamelCase     :Node	,			__UpperCamelCase     :Node | 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       lowerCamelCase			(   self     :Dict	,			__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       lowerCamelCase			(   self     :Tuple	,			__UpperCamelCase     :int						):
												try:
																			self.search(__UpperCamelCase						)
																			return True
												except Exception:
																			return False


					def       lowerCamelCase			(   self     :List[Any]						):
												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       lowerCamelCase			(   self     :List[str]						):
												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       lowerCamelCase			(   self     :str						):
												return self._inorder_traversal(self.root						)


					def       lowerCamelCase			(   self     :List[str]	,			__UpperCamelCase     :Node | None						):
												if node is not None:
																			yield from self._inorder_traversal(node.left						)
																			yield node
																			yield from self._inorder_traversal(node.right						)


					def       lowerCamelCase			(   self     :List[str]						):
												return self._preorder_traversal(self.root						)


					def       lowerCamelCase			(   self     :Any	,			__UpperCamelCase     :Node | None						):
												if node is not None:
																			yield node
																			yield from self._preorder_traversal(node.left						)
																			yield from self._preorder_traversal(node.right						)







class    _UpperCAmelCase  (      unittest.TestCase					):


					@staticmethod
					def       lowerCamelCase			(   ):
												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       lowerCamelCase			(   self     :Optional[int]						):
												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       lowerCamelCase			(   self     :List[str]						):
												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       lowerCamelCase			(   self     :List[str]						):
												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       lowerCamelCase			(   self     :Optional[int]						):
												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       lowerCamelCase			(   self     :Tuple						):
												A						=    self._get_binary_search_tree()
												t.empty()
												assert t.root is None


					def       lowerCamelCase			(   self     :Union[str, Any]						):
												A						=    self._get_binary_search_tree()
												assert not t.is_empty()

												t.empty()
												assert t.is_empty()


					def       lowerCamelCase			(   self     :str						):
												A						=    self._get_binary_search_tree()

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


					def       lowerCamelCase			(   self     :Optional[Any]						):
												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       lowerCamelCase			(   self     :List[Any]						):
												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       lowerCamelCase			(   self     :Tuple						):
												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       lowerCamelCase			(   self     :str						):
												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__							(     ):
							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(
							    "\n            8\n           / \\\n          3   10\n         / \\    \\\n        1   6    14\n           / \\   /\n          4   7 13\n           \\\n            5\n        "			)

							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:"   ,    UpperCamelCase			)

							# Prints all the elements of the list in preorder traversal
							A						=    [i.label for i in t.preorder_traversal()]
							print("Preorder traversal:"   ,    UpperCamelCase			)

							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(
							    "\n          4\n         / \\\n        1   7\n             \\\n              5\n        "			)
							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:"   ,    UpperCamelCase			)

							# 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:"   ,    UpperCamelCase			)

							print("Max. label:"   ,    t.get_max_label()			)
							print("Min. label:"   ,    t.get_min_label()			)


if __name__ == "__main__":
		binary_search_tree_example()









"""simple docstring"""
import inspect
import unittest

from transformers import ResNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available

from ...test_backbone_common import BackboneTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
		import torch
		from torch import nn

		from transformers import ResNetBackbone, ResNetForImageClassification, ResNetModel
		from transformers.models.resnet.modeling_resnet import RESNET_PRETRAINED_MODEL_ARCHIVE_LIST


if is_vision_available():
		from PIL import Image

		from transformers import AutoImageProcessor






class    _UpperCAmelCase  :


					def __init__(   self     :Optional[Any]	,			__UpperCamelCase     :Dict	,			__UpperCamelCase     :Optional[Any]=3	,			__UpperCamelCase     :Optional[int]=32	,			__UpperCamelCase     :str=3	,			__UpperCamelCase     :Union[str, Any]=10	,			__UpperCamelCase     :Union[str, Any]=[10, 20, 30, 40]	,			__UpperCamelCase     :int=[1, 1, 2, 1]	,			__UpperCamelCase     :Dict=True	,			__UpperCamelCase     :Optional[Any]=True	,			__UpperCamelCase     :Any="relu"	,			__UpperCamelCase     :Optional[Any]=3	,			__UpperCamelCase     :int=None	,			__UpperCamelCase     :str=["stage2", "stage3", "stage4"]	,			__UpperCamelCase     :str=[2, 3, 4]	,			):
												A						=    parent
												A						=    batch_size
												A						=    image_size
												A						=    num_channels
												A						=    embeddings_size
												A						=    hidden_sizes
												A						=    depths
												A						=    is_training
												A						=    use_labels
												A						=    hidden_act
												A						=    num_labels
												A						=    scope
												A						=    len(__UpperCamelCase						)
												A						=    out_features
												A						=    out_indices


					def       lowerCamelCase			(   self     :List[Any]						):
												A						=    floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]						)

												A						=    None
												if self.use_labels:
																			A						=    ids_tensor([self.batch_size]	,			self.num_labels						)

												A						=    self.get_config()

												return config, pixel_values, labels


					def       lowerCamelCase			(   self     :Optional[Any]						):
												return ResNetConfig(
												    num_channels=self.num_channels	,			embeddings_size=self.embeddings_size	,			hidden_sizes=self.hidden_sizes	,			depths=self.depths	,			hidden_act=self.hidden_act	,			num_labels=self.num_labels	,			out_features=self.out_features	,			out_indices=self.out_indices	,			)


					def       lowerCamelCase			(   self     :int	,			__UpperCamelCase     :Optional[Any]	,			__UpperCamelCase     :str	,			__UpperCamelCase     :List[Any]						):
												A						=    ResNetModel(config=__UpperCamelCase						)
												model.to(__UpperCamelCase						)
												model.eval()
												A						=    model(__UpperCamelCase						)
												# expected last hidden states: B, C, H // 32, W // 32
												self.parent.assertEqual(
												    result.last_hidden_state.shape	,			(self.batch_size, self.hidden_sizes[-1], self.image_size // 32, self.image_size // 32)	,			)


					def       lowerCamelCase			(   self     :int	,			__UpperCamelCase     :Optional[Any]	,			__UpperCamelCase     :str	,			__UpperCamelCase     :str						):
												A						=    self.num_labels
												A						=    ResNetForImageClassification(__UpperCamelCase						)
												model.to(__UpperCamelCase						)
												model.eval()
												A						=    model(__UpperCamelCase	,			labels=__UpperCamelCase						)
												self.parent.assertEqual(result.logits.shape	,			(self.batch_size, self.num_labels)						)


					def       lowerCamelCase			(   self     :Dict	,			__UpperCamelCase     :Optional[Any]	,			__UpperCamelCase     :Optional[int]	,			__UpperCamelCase     :str						):
												A						=    ResNetBackbone(config=__UpperCamelCase						)
												model.to(__UpperCamelCase						)
												model.eval()
												A						=    model(__UpperCamelCase						)

												# verify feature maps
												self.parent.assertEqual(len(result.feature_maps						)	,			len(config.out_features						)						)
												self.parent.assertListEqual(list(result.feature_maps[0].shape						)	,			[self.batch_size, self.hidden_sizes[1], 4, 4]						)

												# verify channels
												self.parent.assertEqual(len(model.channels						)	,			len(config.out_features						)						)
												self.parent.assertListEqual(model.channels	,			config.hidden_sizes[1:]						)

												# verify backbone works with out_features=None
												A						=    None
												A						=    ResNetBackbone(config=__UpperCamelCase						)
												model.to(__UpperCamelCase						)
												model.eval()
												A						=    model(__UpperCamelCase						)

												# verify feature maps
												self.parent.assertEqual(len(result.feature_maps						)	,			1						)
												self.parent.assertListEqual(list(result.feature_maps[0].shape						)	,			[self.batch_size, self.hidden_sizes[-1], 1, 1]						)

												# verify channels
												self.parent.assertEqual(len(model.channels						)	,			1						)
												self.parent.assertListEqual(model.channels	,			[config.hidden_sizes[-1]]						)


					def       lowerCamelCase			(   self     :List[Any]						):
												A						=    self.prepare_config_and_inputs()
												A,      A,      A						=    config_and_inputs
												A						=    {"pixel_values": pixel_values}
												return config, inputs_dict







@require_torch
class    _UpperCAmelCase  (      lowercase_	,				lowercase_	,				unittest.TestCase					):
					UpperCamelCase						=				(
					    (
					        ResNetModel,
					        ResNetForImageClassification,
					        ResNetBackbone,
					    )
					    if is_torch_available()
					    else ()
					)
					UpperCamelCase						=				(
					    {'''feature-extraction''': ResNetModel, '''image-classification''': ResNetForImageClassification}
					    if is_torch_available()
					    else {}
					)

					UpperCamelCase						=				True
					UpperCamelCase						=				False
					UpperCamelCase						=				False
					UpperCamelCase						=				False
					UpperCamelCase						=				False


					def       lowerCamelCase			(   self     :List[Any]						):
												A						=    ResNetModelTester(self						)
												A						=    ConfigTester(self	,			config_class=__UpperCamelCase	,			has_text_modality=__UpperCamelCase						)


					def       lowerCamelCase			(   self     :List[Any]						):
												self.create_and_test_config_common_properties()
												self.config_tester.create_and_test_config_to_json_string()
												self.config_tester.create_and_test_config_to_json_file()
												self.config_tester.create_and_test_config_from_and_save_pretrained()
												self.config_tester.create_and_test_config_with_num_labels()
												self.config_tester.check_config_can_be_init_without_params()
												self.config_tester.check_config_arguments_init()


					def       lowerCamelCase			(   self     :Union[str, Any]						):
												return


					@unittest.skip(reason="ResNet does not use inputs_embeds"						)
					def       lowerCamelCase			(   self     :Optional[int]						):
												pass


					@unittest.skip(reason="ResNet does not support input and output embeddings"						)
					def       lowerCamelCase			(   self     :Optional[Any]						):
												pass


					def       lowerCamelCase			(   self     :List[Any]						):
												A,      A						=    self.model_tester.prepare_config_and_inputs_for_common()

												for model_class in self.all_model_classes:
																			A						=    model_class(__UpperCamelCase						)
																			A						=    inspect.signature(model.forward						)
																			# signature.parameters is an OrderedDict => so arg_names order is deterministic
																			A						=    [*signature.parameters.keys()]

																			A						=    ["pixel_values"]
																			self.assertListEqual(arg_names[:1]	,			__UpperCamelCase						)


					def       lowerCamelCase			(   self     :Tuple						):
												A						=    self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_model(*__UpperCamelCase						)


					def       lowerCamelCase			(   self     :Union[str, Any]						):
												A						=    self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_backbone(*__UpperCamelCase						)


					def       lowerCamelCase			(   self     :Optional[Any]						):
												A,      A						=    self.model_tester.prepare_config_and_inputs_for_common()

												for model_class in self.all_model_classes:
																			A						=    model_class(config=__UpperCamelCase						)
																			for name, module in model.named_modules():
																										if isinstance(__UpperCamelCase	,			(nn.BatchNormad, nn.GroupNorm)						):
																																	self.assertTrue(
																																	    torch.all(module.weight == 1						)	,			msg=f"Parameter {name} of model {model_class} seems not properly initialized"	,			)
																																	self.assertTrue(
																																	    torch.all(module.bias == 0						)	,			msg=f"Parameter {name} of model {model_class} seems not properly initialized"	,			)


					def       lowerCamelCase			(   self     :Optional[Any]						):
												def check_hidden_states_output(__UpperCamelCase     :int	,			__UpperCamelCase     :Any	,			__UpperCamelCase     :Union[str, Any]						):
																			A						=    model_class(__UpperCamelCase						)
																			model.to(__UpperCamelCase						)
																			model.eval()

																			with torch.no_grad():
																										A						=    model(**self._prepare_for_class(__UpperCamelCase	,			__UpperCamelCase						)						)

																			A						=    outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

																			A						=    self.model_tester.num_stages
																			self.assertEqual(len(__UpperCamelCase						)	,			expected_num_stages + 1						)

																			# ResNet's feature maps are of shape (batch_size, num_channels, height, width)
																			self.assertListEqual(
																			    list(hidden_states[0].shape[-2:]						)	,			[self.model_tester.image_size // 4, self.model_tester.image_size // 4]	,			)

												A,      A						=    self.model_tester.prepare_config_and_inputs_for_common()
												A						=    ["basic", "bottleneck"]
												for model_class in self.all_model_classes:
																			for layer_type in layers_type:
																										A						=    layer_type
																										A						=    True
																										check_hidden_states_output(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase						)

																										# check that output_hidden_states also work using config
																										del inputs_dict["output_hidden_states"]
																										A						=    True

																										check_hidden_states_output(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase						)


					@unittest.skip(reason="ResNet does not use feedforward chunking"						)
					def       lowerCamelCase			(   self     :Tuple						):
												pass


					def       lowerCamelCase			(   self     :Optional[int]						):
												A						=    self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_for_image_classification(*__UpperCamelCase						)


					@slow
					def       lowerCamelCase			(   self     :Union[str, Any]						):
												for model_name in RESNET_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
																			A						=    ResNetModel.from_pretrained(__UpperCamelCase						)
																			self.assertIsNotNone(__UpperCamelCase						)







def    A__							(     ):
							A						=    Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"			)
							return image






@require_torch
@require_vision
class    _UpperCAmelCase  (      unittest.TestCase					):


					@cached_property
					def       lowerCamelCase			(   self     :List[Any]						):
												return (
												    AutoImageProcessor.from_pretrained(RESNET_PRETRAINED_MODEL_ARCHIVE_LIST[0]						)
												    if is_vision_available()
												    else None
												)


					@slow
					def       lowerCamelCase			(   self     :Dict						):
												A						=    ResNetForImageClassification.from_pretrained(RESNET_PRETRAINED_MODEL_ARCHIVE_LIST[0]						).to(__UpperCamelCase						)

												A						=    self.default_image_processor
												A						=    prepare_img()
												A						=    image_processor(images=__UpperCamelCase	,			return_tensors="pt"						).to(__UpperCamelCase						)

												# forward pass
												with torch.no_grad():
																			A						=    model(**__UpperCamelCase						)

												# verify the logits
												A						=    torch.Size((1, 10_00)						)
												self.assertEqual(outputs.logits.shape	,			__UpperCamelCase						)

												A						=    torch.tensor([-11.1_069, -9.7_877, -8.3_777]						).to(__UpperCamelCase						)

												self.assertTrue(torch.allclose(outputs.logits[0, :3]	,			__UpperCamelCase	,			atol=1e-4						)						)







@require_torch
class    _UpperCAmelCase  (      lowercase_	,				unittest.TestCase					):
					UpperCamelCase						=				(ResNetBackbone,) if is_torch_available() else ()
					UpperCamelCase						=				False
					UpperCamelCase						=				ResNetConfig


					def       lowerCamelCase			(   self     :Dict						):
												A						=    ResNetModelTester(self						)


