



'''simple docstring'''






import tempfile

import torch

from diffusers import PNDMScheduler

from .test_schedulers import SchedulerCommonTest

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	lowerCamelCase__			 =       (PNDMScheduler,)
	lowerCamelCase__			 =       (("""num_inference_steps""", 50),)







	def      A	(						self			:     str		,			**__snake_case			:     Tuple		)			->		Any:
								UpperCAmelCase :       Optional[int] 							=		{
								    '''num_train_timesteps''': 1000,
								    '''beta_start''': 0.00_01,
								    '''beta_end''': 0.02,
								    '''beta_schedule''': '''linear''',
								}

								config.update(**__snake_case		)
								return config







	def      A	(						self			:     Optional[Any]		,			__snake_case			:     Optional[Any]=0		,			**__snake_case			:     Tuple		)			->		Union[str, Any]:
								UpperCAmelCase :       List[str] 							=		dict(self.forward_default_kwargs		)
								UpperCAmelCase :       Tuple 							=		kwargs.pop('''num_inference_steps'''		,			__snake_case		)
								UpperCAmelCase :       Tuple 							=		self.dummy_sample
								UpperCAmelCase :       Union[str, Any] 							=		0.1 * sample
								UpperCAmelCase :       Any 							=		[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]

								for scheduler_class in self.scheduler_classes:
															UpperCAmelCase :       Union[str, Any] 							=		self.get_scheduler_config(**__snake_case		)
															UpperCAmelCase :       Dict 							=		scheduler_class(**__snake_case		)
															scheduler.set_timesteps(__snake_case		)
															# copy over dummy past residuals
															UpperCAmelCase :       str 							=		dummy_past_residuals[:]

															with tempfile.TemporaryDirectory() as tmpdirname:
																						scheduler.save_config(__snake_case		)
																						UpperCAmelCase :       List[str] 							=		scheduler_class.from_pretrained(__snake_case		)
																						new_scheduler.set_timesteps(__snake_case		)
																						# copy over dummy past residuals
																						UpperCAmelCase :       Optional[Any] 							=		dummy_past_residuals[:]

															UpperCAmelCase :       int 							=		scheduler.step_prk(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample
															UpperCAmelCase :       Dict 							=		new_scheduler.step_prk(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample

															assert torch.sum(torch.abs(output - new_output		)		) < 1E-5, "Scheduler outputs are not identical"

															UpperCAmelCase :       Optional[Any] 							=		scheduler.step_plms(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample
															UpperCAmelCase :       List[str] 							=		new_scheduler.step_plms(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample

															assert torch.sum(torch.abs(output - new_output		)		) < 1E-5, "Scheduler outputs are not identical"







	def      A	(						self			:     Tuple		)			->		Tuple:
								pass







	def      A	(						self			:     int		,			__snake_case			:     List[Any]=0		,			**__snake_case			:     List[Any]		)			->		Union[str, Any]:
								UpperCAmelCase :       List[Any] 							=		dict(self.forward_default_kwargs		)
								UpperCAmelCase :       Tuple 							=		kwargs.pop('''num_inference_steps'''		,			__snake_case		)
								UpperCAmelCase :       Dict 							=		self.dummy_sample
								UpperCAmelCase :       List[Any] 							=		0.1 * sample
								UpperCAmelCase :       int 							=		[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]

								for scheduler_class in self.scheduler_classes:
															UpperCAmelCase :       Any 							=		self.get_scheduler_config()
															UpperCAmelCase :       Tuple 							=		scheduler_class(**__snake_case		)
															scheduler.set_timesteps(__snake_case		)

															# copy over dummy past residuals (must be after setting timesteps)
															UpperCAmelCase :       Union[str, Any] 							=		dummy_past_residuals[:]

															with tempfile.TemporaryDirectory() as tmpdirname:
																						scheduler.save_config(__snake_case		)
																						UpperCAmelCase :       List[str] 							=		scheduler_class.from_pretrained(__snake_case		)
																						# copy over dummy past residuals
																						new_scheduler.set_timesteps(__snake_case		)

																						# copy over dummy past residual (must be after setting timesteps)
																						UpperCAmelCase :       Dict 							=		dummy_past_residuals[:]

															UpperCAmelCase :       Optional[int] 							=		scheduler.step_prk(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample
															UpperCAmelCase :       List[Any] 							=		new_scheduler.step_prk(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample

															assert torch.sum(torch.abs(output - new_output		)		) < 1E-5, "Scheduler outputs are not identical"

															UpperCAmelCase :       str 							=		scheduler.step_plms(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample
															UpperCAmelCase :       Optional[int] 							=		new_scheduler.step_plms(__snake_case		,			__snake_case		,			__snake_case		,			**__snake_case		).prev_sample

															assert torch.sum(torch.abs(output - new_output		)		) < 1E-5, "Scheduler outputs are not identical"







	def      A	(						self			:     Tuple		,			**__snake_case			:     Tuple		)			->		Any:
								UpperCAmelCase :       Dict 							=		self.scheduler_classes[0]
								UpperCAmelCase :       Tuple 							=		self.get_scheduler_config(**__snake_case		)
								UpperCAmelCase :       Tuple 							=		scheduler_class(**__snake_case		)

								UpperCAmelCase :       Any 							=		10
								UpperCAmelCase :       Optional[Any] 							=		self.dummy_model()
								UpperCAmelCase :       int 							=		self.dummy_sample_deter
								scheduler.set_timesteps(__snake_case		)

								for i, t in enumerate(scheduler.prk_timesteps		):
															UpperCAmelCase :       Tuple 							=		model(__snake_case		,			__snake_case		)
															UpperCAmelCase :       int 							=		scheduler.step_prk(__snake_case		,			__snake_case		,			__snake_case		).prev_sample

								for i, t in enumerate(scheduler.plms_timesteps		):
															UpperCAmelCase :       Any 							=		model(__snake_case		,			__snake_case		)
															UpperCAmelCase :       Any 							=		scheduler.step_plms(__snake_case		,			__snake_case		,			__snake_case		).prev_sample

								return sample







	def      A	(						self			:     Optional[int]		)			->		Optional[int]:
								UpperCAmelCase :       Union[str, Any] 							=		dict(self.forward_default_kwargs		)

								UpperCAmelCase :       Dict 							=		kwargs.pop('''num_inference_steps'''		,			__snake_case		)

								for scheduler_class in self.scheduler_classes:
															UpperCAmelCase :       List[Any] 							=		self.get_scheduler_config()
															UpperCAmelCase :       int 							=		scheduler_class(**__snake_case		)

															UpperCAmelCase :       List[str] 							=		self.dummy_sample
															UpperCAmelCase :       Any 							=		0.1 * sample

															if num_inference_steps is not None and hasattr(__snake_case		,			'''set_timesteps'''		):
																						scheduler.set_timesteps(__snake_case		)
															elif num_inference_steps is not None and not hasattr(__snake_case		,			'''set_timesteps'''		):
																						UpperCAmelCase :       List[Any] 							=		num_inference_steps

															# copy over dummy past residuals (must be done after set_timesteps)
															UpperCAmelCase :       Optional[int] 							=		[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]
															UpperCAmelCase :       Optional[int] 							=		dummy_past_residuals[:]

															UpperCAmelCase :       List[Any] 							=		scheduler.step_prk(__snake_case		,			0		,			__snake_case		,			**__snake_case		).prev_sample
															UpperCAmelCase :       Optional[Any] 							=		scheduler.step_prk(__snake_case		,			1		,			__snake_case		,			**__snake_case		).prev_sample

															self.assertEqual(output_a.shape		,			sample.shape		)
															self.assertEqual(output_a.shape		,			output_a.shape		)

															UpperCAmelCase :       str 							=		scheduler.step_plms(__snake_case		,			0		,			__snake_case		,			**__snake_case		).prev_sample
															UpperCAmelCase :       List[str] 							=		scheduler.step_plms(__snake_case		,			1		,			__snake_case		,			**__snake_case		).prev_sample

															self.assertEqual(output_a.shape		,			sample.shape		)
															self.assertEqual(output_a.shape		,			output_a.shape		)







	def      A	(						self			:     List[str]		)			->		List[Any]:
								for timesteps in [100, 1000]:
															self.check_over_configs(num_train_timesteps=__snake_case		)







	def      A	(						self			:     Any		)			->		Dict:
								for steps_offset in [0, 1]:
															self.check_over_configs(steps_offset=__snake_case		)

								UpperCAmelCase :       Union[str, Any] 							=		self.scheduler_classes[0]
								UpperCAmelCase :       str 							=		self.get_scheduler_config(steps_offset=1		)
								UpperCAmelCase :       Tuple 							=		scheduler_class(**__snake_case		)
								scheduler.set_timesteps(10		)
								assert torch.equal(
								    scheduler.timesteps		,			torch.LongTensor(
								        [901, 851, 851, 801, 801, 751, 751, 701, 701, 651, 651, 601, 601, 501, 401, 301, 201, 101, 1]		)		,			)







	def      A	(						self			:     int		)			->		Optional[Any]:
								for beta_start, beta_end in zip([0.00_01, 0.0_01]		,			[0.0_02, 0.02]		):
															self.check_over_configs(beta_start=__snake_case		,			beta_end=__snake_case		)







	def      A	(						self			:     List[Any]		)			->		Optional[Any]:
								for schedule in ["linear", "squaredcos_cap_v2"]:
															self.check_over_configs(beta_schedule=__snake_case		)







	def      A	(						self			:     int		)			->		Optional[Any]:
								for prediction_type in ["epsilon", "v_prediction"]:
															self.check_over_configs(prediction_type=__snake_case		)







	def      A	(						self			:     Any		)			->		Any:
								for t in [1, 5, 10]:
															self.check_over_forward(time_step=__snake_case		)







	def      A	(						self			:     Dict		)			->		int:
								for t, num_inference_steps in zip([1, 5, 10]		,			[10, 50, 100]		):
															self.check_over_forward(num_inference_steps=__snake_case		)







	def      A	(						self			:     List[Any]		)			->		int:
								# earlier version of set_timesteps() caused an error indexing alpha's with inference steps as power of 3
								UpperCAmelCase :       str 							=		27

								for scheduler_class in self.scheduler_classes:
															UpperCAmelCase :       Tuple 							=		self.dummy_sample
															UpperCAmelCase :       List[Any] 							=		0.1 * sample

															UpperCAmelCase :       Optional[int] 							=		self.get_scheduler_config()
															UpperCAmelCase :       int 							=		scheduler_class(**__snake_case		)

															scheduler.set_timesteps(__snake_case		)

															# before power of 3 fix, would error on first step, so we only need to do two
															for i, t in enumerate(scheduler.prk_timesteps[:2]		):
																						UpperCAmelCase :       str 							=		scheduler.step_prk(__snake_case		,			__snake_case		,			__snake_case		).prev_sample







	def      A	(						self			:     Optional[int]		)			->		Optional[int]:
								with self.assertRaises(__snake_case		):
															UpperCAmelCase :       Optional[int] 							=		self.scheduler_classes[0]
															UpperCAmelCase :       List[str] 							=		self.get_scheduler_config()
															UpperCAmelCase :       List[str] 							=		scheduler_class(**__snake_case		)

															scheduler.step_plms(self.dummy_sample		,			1		,			self.dummy_sample		).prev_sample







	def      A	(						self			:     Tuple		)			->		List[str]:
								UpperCAmelCase :       Union[str, Any] 							=		self.full_loop()
								UpperCAmelCase :       str 							=		torch.sum(torch.abs(__snake_case		)		)
								UpperCAmelCase :       List[str] 							=		torch.mean(torch.abs(__snake_case		)		)

								assert abs(result_sum.item() - 1_98.13_18		) < 1E-2
								assert abs(result_mean.item() - 0.25_80		) < 1E-3







	def      A	(						self			:     Union[str, Any]		)			->		Dict:
								UpperCAmelCase :       int 							=		self.full_loop(prediction_type='''v_prediction'''		)
								UpperCAmelCase :       List[Any] 							=		torch.sum(torch.abs(__snake_case		)		)
								UpperCAmelCase :       Dict 							=		torch.mean(torch.abs(__snake_case		)		)

								assert abs(result_sum.item() - 67.39_86		) < 1E-2
								assert abs(result_mean.item() - 0.08_78		) < 1E-3







	def      A	(						self			:     Any		)			->		List[str]:
								# We specify different beta, so that the first alpha is 0.99
								UpperCAmelCase :       int 							=		self.full_loop(set_alpha_to_one=__snake_case		,			beta_start=0.01		)
								UpperCAmelCase :       Optional[int] 							=		torch.sum(torch.abs(__snake_case		)		)
								UpperCAmelCase :       str 							=		torch.mean(torch.abs(__snake_case		)		)

								assert abs(result_sum.item() - 2_30.03_99		) < 1E-2
								assert abs(result_mean.item() - 0.29_95		) < 1E-3







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

								assert abs(result_sum.item() - 1_86.94_82		) < 1E-2
								assert abs(result_mean.item() - 0.24_34		) < 1E-3









'''simple docstring'''


from typing import Any





class     lowercase__  :





							'''simple docstring'''


							def __init__(    self    ,					__snake_case  ):
											_SCREAMING_SNAKE_CASE :       Dict     		=      data
											_SCREAMING_SNAKE_CASE :       Optional[int]     		=      None






							def __repr__(    self  ):
											return f"""Node({self.data})"""





class     lowercase__  :





							'''simple docstring'''


							def __init__(    self  ):
											_SCREAMING_SNAKE_CASE :       Any     		=      None






							def __iter__(    self  ):
											_SCREAMING_SNAKE_CASE :       Any     		=      self.head
											while node:
															yield node.data
															_SCREAMING_SNAKE_CASE :       List[Any]     		=      node.next






							def __len__(    self  ):
											return sum(1 for _ in self  )






							def __repr__(    self  ):
											return "->".join([str(__snake_case  ) for item in self]  )






							def __getitem__(    self    ,					__snake_case  ):
											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    ,					__snake_case    ,					__snake_case  ):
											if not 0 <= index < len(self  ):
															raise ValueError("""list index out of range."""  )
											_SCREAMING_SNAKE_CASE :       Any     		=      self.head
											for _ in range(__snake_case  ):
															_SCREAMING_SNAKE_CASE :       List[Any]     		=      current.next
											_SCREAMING_SNAKE_CASE :       Dict     		=      data






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											self.insert_nth(len(self  )    ,					__snake_case  )






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											self.insert_nth(0    ,					__snake_case  )






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






							def UpperCAmelCase_	(    self  ):  # print every node data
											print(self  )






							def UpperCAmelCase_	(    self  ):
											return self.delete_nth(0  )






							def UpperCAmelCase_	(    self  ):  # delete from tail
											return self.delete_nth(len(self  ) - 1  )






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






							def UpperCAmelCase_	(    self  ):
											return self.head is None






							def UpperCAmelCase_	(    self  ):
											_SCREAMING_SNAKE_CASE :       Dict     		=      None
											_SCREAMING_SNAKE_CASE :       int     		=      self.head

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







def 			snake_case_   (  ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE :       Dict     		=      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     ):
								_SCREAMING_SNAKE_CASE :       List[str]     		=      -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 			snake_case_   (  ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE :       Optional[int]     		=      [
				    -9,
				    100,
				    Node(7734_5112     ),
				    """dlrow olleH""",
				    7,
				    5555,
				    0,
				    -1_9_2.5_5_5_5_5,
				    """Hello, world!""",
				    7_7.9,
				    Node(10     ),
				    None,
				    None,
				    1_2.2_0,
				]
				_SCREAMING_SNAKE_CASE :       Optional[int]     		=      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
				_SCREAMING_SNAKE_CASE :       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
				_SCREAMING_SNAKE_CASE :       List[Any]     		=      linked_list.delete_tail()
				assert result == 1_2.2
				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
				_SCREAMING_SNAKE_CASE :       Optional[int]     		=      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 			snake_case_   (  ):







				"""simple docstring"""





				from doctest import testmod

				testmod()

				_SCREAMING_SNAKE_CASE :       Optional[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]}"""     )
				_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      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()




