



from typing import Any



class     UpperCAmelCase_       :







							def __init__(  self,     __a):

														'''simple docstring'''

														_lowerCAmelCase	:				List[Any]					  =       data
														_lowerCAmelCase	:				List[str]					  =       None







							def __repr__(  self):

														'''simple docstring'''

														return f"Node({self.data})"



class     UpperCAmelCase_       :







							def __init__(  self):

														'''simple docstring'''

														_lowerCAmelCase	:				int					  =       None







							def __iter__(  self):

														'''simple docstring'''

														_lowerCAmelCase	:				Optional[int]					  =       self.head
														while node:
																					yield node.data
																					_lowerCAmelCase	:				Dict					  =       node.next







							def __len__(  self):

														'''simple docstring'''

														return sum(1 for _ in self)







							def __repr__(  self):

														'''simple docstring'''

														return "->".join([str(lowerCAmelCase_) for item in self])







							def __getitem__(  self,     __a):

														'''simple docstring'''

														if not 0 <= index < len(self):
																					raise ValueError("list index out of range.")
														for i, node in enumerate(self):
																					if i == index:
																												return node
														return None







							def __setitem__(  self,     __a,     __a):

														'''simple docstring'''

														if not 0 <= index < len(self):
																					raise ValueError("list index out of range.")
														_lowerCAmelCase	:				List[str]					  =       self.head
														for _ in range(lowerCAmelCase_):
																					_lowerCAmelCase	:				Tuple					  =       current.next
														_lowerCAmelCase	:				Any					  =       data







							def   snake_case__ (  self,     __a):

														'''simple docstring'''

														self.insert_nth(len(self),     lowerCAmelCase_)







							def   snake_case__ (  self,     __a):

														'''simple docstring'''

														self.insert_nth(0,     lowerCAmelCase_)







							def   snake_case__ (  self,     __a,     __a):

														'''simple docstring'''

														if not 0 <= index <= len(self):
																					raise IndexError("list index out of range")
														_lowerCAmelCase	:				Dict					  =       Node(lowerCAmelCase_)
														if self.head is None:
																					_lowerCAmelCase	:				Tuple					  =       new_node
														elif index == 0:
																					_lowerCAmelCase	:				List[Any]					  =       self.head  # link new_node to head
																					_lowerCAmelCase	:				List[Any]					  =       new_node
														else:
																					_lowerCAmelCase	:				List[Any]					  =       self.head
																					for _ in range(index - 1):
																												_lowerCAmelCase	:				Dict					  =       temp.next
																					_lowerCAmelCase	:				List[str]					  =       temp.next
																					_lowerCAmelCase	:				Optional[int]					  =       new_node







							def   snake_case__ (  self):  # print every node data

														'''simple docstring'''

														print(self)







							def   snake_case__ (  self):

														'''simple docstring'''

														return self.delete_nth(0)







							def   snake_case__ (  self):  # delete from tail

														'''simple docstring'''

														return self.delete_nth(len(self) - 1)







							def   snake_case__ (  self,     __a = 0):

														'''simple docstring'''

														if not 0 <= index <= len(self) - 1:  # test if index is valid
																					raise IndexError("List index out of range.")
														_lowerCAmelCase	:				Union[str, Any]					  =       self.head  # default first node
														if index == 0:
																					_lowerCAmelCase	:				Optional[int]					  =       self.head.next
														else:
																					_lowerCAmelCase	:				Tuple					  =       self.head
																					for _ in range(index - 1):
																												_lowerCAmelCase	:				Optional[int]					  =       temp.next
																					_lowerCAmelCase	:				List[str]					  =       temp.next
																					_lowerCAmelCase	:				List[str]					  =       temp.next.next
														return delete_node.data







							def   snake_case__ (  self):

														'''simple docstring'''

														return self.head is None







							def   snake_case__ (  self):

														'''simple docstring'''

														_lowerCAmelCase	:				List[str]					  =       None
														_lowerCAmelCase	:				str					  =       self.head

														while current:
																					# Store the current node's next node.
																					_lowerCAmelCase	:				Union[str, Any]					  =       current.next
																					# Make the current node's next point backwards
																					_lowerCAmelCase	:				Dict					  =       prev
																					# Make the previous node be the current node
																					_lowerCAmelCase	:				Optional[int]					  =       current
																					# Make the current node the next node (to progress iteration)
																					_lowerCAmelCase	:				str					  =       next_node
														# Return prev in order to put the head at the end
														_lowerCAmelCase	:				Dict					  =       prev






def 							A							(   ):





							'''simple docstring'''




							_lowerCAmelCase	:				List[Any]					  =       LinkedList()
							assert linked_list.is_empty() is True
							assert str(_SCREAMING_SNAKE_CASE    ) == ""

							try:
														linked_list.delete_head()
														raise AssertionError  # This should not happen.
							except IndexError:
														assert True  # This should happen.

							try:
														linked_list.delete_tail()
														raise AssertionError  # This should not happen.
							except IndexError:
														assert True  # This should happen.

							for i in range(10    ):
														assert len(_SCREAMING_SNAKE_CASE    ) == i
														linked_list.insert_nth(_SCREAMING_SNAKE_CASE							,					i + 1    )
							assert str(_SCREAMING_SNAKE_CASE    ) == "->".join(str(_SCREAMING_SNAKE_CASE    ) for i in range(1							,					11    )    )

							linked_list.insert_head(0    )
							linked_list.insert_tail(11    )
							assert str(_SCREAMING_SNAKE_CASE    ) == "->".join(str(_SCREAMING_SNAKE_CASE    ) for i in range(0							,					12    )    )

							assert linked_list.delete_head() == 0
							assert linked_list.delete_nth(9    ) == 10
							assert linked_list.delete_tail() == 11
							assert len(_SCREAMING_SNAKE_CASE    ) == 9
							assert str(_SCREAMING_SNAKE_CASE    ) == "->".join(str(_SCREAMING_SNAKE_CASE    ) for i in range(1							,					10    )    )

							assert all(linked_list[i] == i + 1 for i in range(0							,					9    )    ) is True

							for i in range(0							,					9    ):
														_lowerCAmelCase	:				Optional[int]					  =       -i
							assert all(linked_list[i] == -i for i in range(0							,					9    )    ) is True

							linked_list.reverse()
							assert str(_SCREAMING_SNAKE_CASE    ) == "->".join(str(_SCREAMING_SNAKE_CASE    ) for i in range(-8							,					1    )    )






def 							A							(   ):





							'''simple docstring'''




							_lowerCAmelCase	:				Tuple					  =       [
							    -9,
							    100,
							    Node(77_345_112    ),
							    "dlrow olleH",
							    7,
							    5_555,
							    0,
							    -192.55_555,
							    "Hello, world!",
							    77.9,
							    Node(10    ),
							    None,
							    None,
							    12.20,
							]
							_lowerCAmelCase	:				Dict					  =       LinkedList()

							for i in test_input:
														linked_list.insert_tail(_SCREAMING_SNAKE_CASE    )

							# Check if it's empty or not
							assert linked_list.is_empty() is False
							assert (
							    str(_SCREAMING_SNAKE_CASE    ) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
							    "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
							)

							# Delete the head
							_lowerCAmelCase	:				List[Any]					  =       linked_list.delete_head()
							assert result == -9
							assert (
							    str(_SCREAMING_SNAKE_CASE    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
							    "Hello, world!->77.9->Node(10)->None->None->12.2"
							)

							# Delete the tail
							_lowerCAmelCase	:				int					  =       linked_list.delete_tail()
							assert result == 12.2
							assert (
							    str(_SCREAMING_SNAKE_CASE    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
							    "Hello, world!->77.9->Node(10)->None->None"
							)

							# Delete a node in specific location in linked list
							_lowerCAmelCase	:				List[Any]					  =       linked_list.delete_nth(10    )
							assert result is None
							assert (
							    str(_SCREAMING_SNAKE_CASE    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
							    "Hello, world!->77.9->Node(10)->None"
							)

							# Add a Node instance to its head
							linked_list.insert_head(Node("Hello again, world!"    )    )
							assert (
							    str(_SCREAMING_SNAKE_CASE    )
							    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
							    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
							)

							# Add None to its tail
							linked_list.insert_tail(_SCREAMING_SNAKE_CASE    )
							assert (
							    str(_SCREAMING_SNAKE_CASE    )
							    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
							    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
							)

							# Reverse the linked list
							linked_list.reverse()
							assert (
							    str(_SCREAMING_SNAKE_CASE    )
							    == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
							    "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
							)






def 							A							(   ):





							'''simple docstring'''




							from doctest import testmod

							testmod()

							_lowerCAmelCase	:				int					  =       LinkedList()
							linked_list.insert_head(input("Inserting 1st at head "    ).strip()    )
							linked_list.insert_head(input("Inserting 2nd at head "    ).strip()    )
							print("\nPrint list:"    )
							linked_list.print_list()
							linked_list.insert_tail(input("\nInserting 1st at tail "    ).strip()    )
							linked_list.insert_tail(input("Inserting 2nd at tail "    ).strip()    )
							print("\nPrint list:"    )
							linked_list.print_list()
							print("\nDelete head"    )
							linked_list.delete_head()
							print("Delete tail"    )
							linked_list.delete_tail()
							print("\nPrint list:"    )
							linked_list.print_list()
							print("\nReverse linked list"    )
							linked_list.reverse()
							print("\nPrint list:"    )
							linked_list.print_list()
							print("\nString representation of linked list:"    )
							print(_SCREAMING_SNAKE_CASE    )
							print("\nReading/changing Node data using indexing:"    )
							print(F"Element at Position 1: {linked_list[1]}"    )
							_lowerCAmelCase	:				Dict					  =       input("Enter New Value: "    ).strip()
							print("New list:"    )
							print(_SCREAMING_SNAKE_CASE    )
							print(F"length of linked_list is : {len(_SCREAMING_SNAKE_CASE    )}"    )


if __name__ == "__main__":
						main()




'''simple docstring'''





import unittest
from typing import Dict, List, Optional, Union

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
					import torch

if is_vision_available():
					from PIL import Image

					from transformers import BridgeTowerImageProcessor
class 						a__					(					unittest.TestCase   ):





			'''simple docstring'''

			def __init__(  self							:			str			,    lowerCAmelCase_							:			str			,    lowerCAmelCase_							:			bool = True			,    lowerCAmelCase_							:			Dict[str, int] = None			,    lowerCAmelCase_							:			int = 32			,    lowerCAmelCase_							:			bool = True			,    lowerCAmelCase_							:			Union[int, float] = 1 / 255			,    lowerCAmelCase_							:			bool = True			,    lowerCAmelCase_							:			bool = True			,    lowerCAmelCase_							:			Optional[Union[float, List[float]]] = [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73]			,    lowerCAmelCase_							:			Optional[Union[float, List[float]]] = [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11]			,    lowerCAmelCase_							:			bool = True			,    lowerCAmelCase_							:			str=7			,    lowerCAmelCase_							:			Union[str, Any]=30			,    lowerCAmelCase_							:			str=400			,    lowerCAmelCase_							:			int=3			,    )      ->		str:
						__A=	parent
						__A=	do_resize
						__A=	size if size is not None else {'shortest_edge': 288}
						__A=	size_divisor
						__A=	do_rescale
						__A=	rescale_factor
						__A=	do_normalize
						__A=	do_center_crop
						__A=	image_mean
						__A=	image_std
						__A=	do_pad
						__A=	batch_size
						__A=	num_channels
						__A=	min_resolution
						__A=	max_resolution
			def 					lowerCAmelCase     (  self							:			Union[str, Any]	)      ->		int:
						return {
						    "image_mean": self.image_mean,
						    "image_std": self.image_std,
						    "do_normalize": self.do_normalize,
						    "do_resize": self.do_resize,
						    "size": self.size,
						    "size_divisor": self.size_divisor,
						}

			def 					lowerCAmelCase     (  self							:			Dict			,    lowerCAmelCase_							:			str			,    lowerCAmelCase_							:			str=False	)      ->		str:
						if not batched:
									__A=	self.size['shortest_edge']
									__A=	image_inputs[0]
									if isinstance(lowerCAmelCase_			,    Image.Image	):
												__A,	__A=	image.size
									else:
												__A,	__A=	image.shape[1], image.shape[2]
									__A=	size / min(lowerCAmelCase_			,    lowerCAmelCase_	)
									if h < w:
												__A,	__A=	size, scale * w
									else:
												__A,	__A=	scale * h, size

									__A=	int((1_333 / 800) * size	)
									if max(lowerCAmelCase_			,    lowerCAmelCase_	) > max_size:
												__A=	max_size / max(lowerCAmelCase_			,    lowerCAmelCase_	)
												__A=	newh * scale
												__A=	neww * scale

									__A,	__A=	int(newh + 0.5	), int(neww + 0.5	)
									__A,	__A=	(
									    newh // self.size_divisor * self.size_divisor,
									    neww // self.size_divisor * self.size_divisor,
									)

						else:
									__A=	[]
									for image in image_inputs:
												__A,	__A=	self.get_expected_values([image]	)
												expected_values.append((expected_height, expected_width)	)
									__A=	max(lowerCAmelCase_			,    key=lambda lowerCAmelCase_	: item[0]	)[0]
									__A=	max(lowerCAmelCase_			,    key=lambda lowerCAmelCase_	: item[1]	)[1]

						return expected_height, expected_width


@require_torch
@require_vision
class 						a__					(					a_      ,  unittest.TestCase   ):





			'''simple docstring'''

			A						:				int					      =			BridgeTowerImageProcessor if is_vision_available() else None
			def 					lowerCAmelCase     (  self							:			Dict	)      ->		Optional[int]:
						__A=	BridgeTowerImageProcessingTester(self	)
			@property
			def 					lowerCAmelCase     (  self							:			Union[str, Any]	)      ->		Union[str, Any]:
						return self.image_processor_tester.prepare_image_processor_dict()
			def 					lowerCAmelCase     (  self							:			Tuple	)      ->		List[Any]:
						__A=	self.image_processing_class(**self.image_processor_dict	)
						self.assertTrue(hasattr(lowerCAmelCase_			,    'image_mean'	)	)
						self.assertTrue(hasattr(lowerCAmelCase_			,    'image_std'	)	)
						self.assertTrue(hasattr(lowerCAmelCase_			,    'do_normalize'	)	)
						self.assertTrue(hasattr(lowerCAmelCase_			,    'do_resize'	)	)
						self.assertTrue(hasattr(lowerCAmelCase_			,    'size'	)	)
						self.assertTrue(hasattr(lowerCAmelCase_			,    'size_divisor'	)	)
			def 					lowerCAmelCase     (  self							:			Optional[Any]	)      ->		str:
						pass
			def 					lowerCAmelCase     (  self							:			Union[str, Any]	)      ->		Any:
						# Initialize image processor
						__A=	self.image_processing_class(**self.image_processor_dict	)
						# create random PIL images
						__A=	prepare_image_inputs(self.image_processor_tester			,    equal_resolution=lowerCAmelCase_	)
						for image in image_inputs:
									self.assertIsInstance(lowerCAmelCase_			,    Image.Image	)

						# Test not batched input
						__A=	image_processing(image_inputs[0]			,    return_tensors='pt'	).pixel_values

						__A,	__A=	self.image_processor_tester.get_expected_values(lowerCAmelCase_	)
						self.assertEqual(
						    encoded_images.shape			,    (1, self.image_processor_tester.num_channels, expected_height, expected_width)			,    )

						# Test batched
						__A=	image_processing(lowerCAmelCase_			,    return_tensors='pt'	).pixel_values

						__A,	__A=	self.image_processor_tester.get_expected_values(lowerCAmelCase_			,    batched=lowerCAmelCase_	)
						self.assertEqual(
						    encoded_images.shape			,    (
						        self.image_processor_tester.batch_size,
						        self.image_processor_tester.num_channels,
						        expected_height,
						        expected_width,
						    )			,    )
			def 					lowerCAmelCase     (  self							:			Any	)      ->		Any:
						# Initialize image processor
						__A=	self.image_processing_class(**self.image_processor_dict	)
						# create random numpy tensors
						__A=	prepare_image_inputs(self.image_processor_tester			,    equal_resolution=lowerCAmelCase_			,    numpify=lowerCAmelCase_	)
						for image in image_inputs:
									self.assertIsInstance(lowerCAmelCase_			,    np.ndarray	)

						# Test not batched input
						__A=	image_processing(image_inputs[0]			,    return_tensors='pt'	).pixel_values

						__A,	__A=	self.image_processor_tester.get_expected_values(lowerCAmelCase_	)
						self.assertEqual(
						    encoded_images.shape			,    (1, self.image_processor_tester.num_channels, expected_height, expected_width)			,    )

						# Test batched
						__A=	image_processing(lowerCAmelCase_			,    return_tensors='pt'	).pixel_values

						__A,	__A=	self.image_processor_tester.get_expected_values(lowerCAmelCase_			,    batched=lowerCAmelCase_	)
						self.assertEqual(
						    encoded_images.shape			,    (
						        self.image_processor_tester.batch_size,
						        self.image_processor_tester.num_channels,
						        expected_height,
						        expected_width,
						    )			,    )

			def 					lowerCAmelCase     (  self							:			List[Any]	)      ->		Tuple:
						# Initialize image processor
						__A=	self.image_processing_class(**self.image_processor_dict	)
						# create random PyTorch tensors
						__A=	prepare_image_inputs(self.image_processor_tester			,    equal_resolution=lowerCAmelCase_			,    torchify=lowerCAmelCase_	)
						for image in image_inputs:
									self.assertIsInstance(lowerCAmelCase_			,    torch.Tensor	)

						# Test not batched input
						__A=	image_processing(image_inputs[0]			,    return_tensors='pt'	).pixel_values

						__A,	__A=	self.image_processor_tester.get_expected_values(lowerCAmelCase_	)
						self.assertEqual(
						    encoded_images.shape			,    (1, self.image_processor_tester.num_channels, expected_height, expected_width)			,    )

						# Test batched
						__A=	image_processing(lowerCAmelCase_			,    return_tensors='pt'	).pixel_values

						__A,	__A=	self.image_processor_tester.get_expected_values(lowerCAmelCase_			,    batched=lowerCAmelCase_	)
						self.assertEqual(
						    encoded_images.shape			,    (
						        self.image_processor_tester.batch_size,
						        self.image_processor_tester.num_channels,
						        expected_height,
						        expected_width,
						    )			,    )



