
'''simple docstring'''







class 				lowerCAmelCase__     :






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Optional[int]									= data
											lowercase_			:  str									= None
											lowercase_			:  Union[str, Any]									= None






					def __str__(     self	):


											"""simple docstring"""





											return F'''{self.data}'''







class 				lowerCAmelCase__     :






					def __init__(     self	):


											"""simple docstring"""





											lowercase_			:  Any									= None
											lowercase_			:  List[Any]									= None






					def __iter__(     self	):


											"""simple docstring"""





											lowercase_			:  List[Any]									= self.head
											while node:
																	yield node.data
																	lowercase_			:  Dict									= node.next






					def __str__(     self	):


											"""simple docstring"""





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






					def __len__(     self	):


											"""simple docstring"""





											return sum(1 for _ in self	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											self.insert_at_nth(0       ,							__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											self.insert_at_nth(len(self	)       ,							__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  List[Any]									= len(self	)

											if not 0 <= index <= length:
																	raise IndexError('''list index out of range'''	)
											lowercase_			:  Dict									= Node(__SCREAMING_SNAKE_CASE	)
											if self.head is None:
																	lowercase_			:  Optional[Any]									= new_node
											elif index == 0:
																	lowercase_			:  Optional[Any]									= new_node
																	lowercase_			:  Union[str, Any]									= self.head
																	lowercase_			:  Union[str, Any]									= new_node
											elif index == length:
																	lowercase_			:  List[str]									= new_node
																	lowercase_			:  str									= self.tail
																	lowercase_			:  List[Any]									= new_node
											else:
																	lowercase_			:  List[Any]									= self.head
																	for _ in range(0       ,							__SCREAMING_SNAKE_CASE	):
																							lowercase_			:  Union[str, Any]									= temp.next
																	lowercase_			:  int									= new_node
																	lowercase_			:  List[Any]									= temp.previous
																	lowercase_			:  int									= temp
																	lowercase_			:  List[Any]									= new_node






					def 			_snake_case					(     self	):


											"""simple docstring"""





											return self.delete_at_nth(0	)






					def 			_snake_case					(     self	):


											"""simple docstring"""





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






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Union[str, Any]									= len(self	)

											if not 0 <= index <= length - 1:
																	raise IndexError('''list index out of range'''	)
											lowercase_			:  List[Any]									= self.head  # default first node
											if length == 1:
																	lowercase_			:  Optional[int]									= None
											elif index == 0:
																	lowercase_			:  Any									= self.head.next
																	lowercase_			:  Tuple									= None
											elif index == length - 1:
																	lowercase_			:  Any									= self.tail
																	lowercase_			:  List[Any]									= self.tail.previous
																	lowercase_			:  Optional[Any]									= None
											else:
																	lowercase_			:  Any									= self.head
																	for _ in range(0       ,							__SCREAMING_SNAKE_CASE	):
																							lowercase_			:  List[str]									= temp.next
																	lowercase_			:  Union[str, Any]									= temp
																	lowercase_			:  Dict									= temp.previous
																	lowercase_			:  Dict									= temp.next
											return delete_node.data






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Union[str, Any]									= self.head

											while current.data != data:  # Find the position to delete
																	if current.next:
																							lowercase_			:  List[str]									= current.next
																	else:  # We have reached the end an no value matches
																							raise ValueError('''No data matching given value'''	)

											if current == self.head:
																	self.delete_head()

											elif current == self.tail:
																	self.delete_tail()

											else:  # Before: 1 <--> 2(current) <--> 3
																	lowercase_			:  Dict									= current.next  # 1 --> 3
																	lowercase_			:  str									= current.previous  # 1 <--> 3
											return data






					def 			_snake_case					(     self	):


											"""simple docstring"""





											return len(self	) == 0







def       snake_case_	(       ):



						"""simple docstring"""





						lowercase_			:  Union[str, Any]									= DoublyLinkedList()
						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_at_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_at_head(0							)
						linked_list.insert_at_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_at_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							)							)


if __name__ == "__main__":
							from doctest import testmod

							testmod()





'''simple docstring'''







from typing import List

from ...processing_utils import ProcessorMixin
from ...utils import is_torch_available


if is_torch_available():
							import torch






class 				lowerCAmelCase__     (						lowerCamelCase_  ):
					lowerCAmelCase_       =  ['''image_processor''', '''tokenizer''']
					lowerCAmelCase_       =  '''OneFormerImageProcessor'''
					lowerCAmelCase_       =  ('''CLIPTokenizer''', '''CLIPTokenizerFast''')






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE = 77       ,							__SCREAMING_SNAKE_CASE = 77       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											if image_processor is None:
																	raise ValueError('''You need to specify an `image_processor`.'''	)
											if tokenizer is None:
																	raise ValueError('''You need to specify a `tokenizer`.'''	)

											lowercase_			:  Dict									= max_seq_length
											lowercase_			:  Dict									= task_seq_length

											super().__init__(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=77	):


											"""simple docstring"""





											if text_list is None:
																	raise ValueError('''tokens cannot be None.'''	)

											lowercase_			:  str									= self.tokenizer(__SCREAMING_SNAKE_CASE       ,							padding='''max_length'''       ,							max_length=__SCREAMING_SNAKE_CASE       ,							truncation=__SCREAMING_SNAKE_CASE	)

											lowercase_		,				lowercase_			:  List[str]									= tokens['''attention_mask'''], tokens['''input_ids''']

											lowercase_			:  List[str]									= []
											for attn_mask, input_id in zip(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	):
																	lowercase_			:  Optional[Any]									= torch.tensor(__SCREAMING_SNAKE_CASE	) * torch.tensor(__SCREAMING_SNAKE_CASE	)
																	token_inputs.append(token.unsqueeze(0	)	)

											lowercase_			:  str									= torch.cat(__SCREAMING_SNAKE_CASE       ,							dim=0	)
											return token_inputs






					def __call__(     self       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											if task_inputs is None:
																	raise ValueError('''You have to specify the task_input. Found None.'''	)
											elif images is None:
																	raise ValueError('''You have to specify the image. Found None.'''	)

											if not all(task in ['''semantic''', '''instance''', '''panoptic'''] for task in task_inputs	):
																	raise ValueError('''task_inputs must be semantic, instance, or panoptic.'''	)

											lowercase_			:  Optional[int]									= self.image_processor(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)

											if isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	):
																	lowercase_			:  List[str]									= [task_inputs]

											if isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	) and all(isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	) for task_input in task_inputs	):
																	lowercase_			:  List[str]									= []
																	for task in task_inputs:
																							lowercase_			:  Tuple									= F'''the task is {task}'''
																							task_token_inputs.append(__SCREAMING_SNAKE_CASE	)
																	lowercase_			:  Tuple									= self._preprocess_text(__SCREAMING_SNAKE_CASE       ,							max_length=self.task_seq_length	)
											else:
																	raise TypeError('''Task Inputs should be a string or a list of strings.'''	)

											if hasattr(__SCREAMING_SNAKE_CASE       ,							'''text_inputs'''	):
																	lowercase_			:  Any									= encoded_inputs.text_inputs

																	lowercase_			:  int									= []
																	for texts in texts_list:
																							lowercase_			:  Any									= self._preprocess_text(__SCREAMING_SNAKE_CASE       ,							max_length=self.max_seq_length	)
																							text_inputs.append(text_input_list.unsqueeze(0	)	)

																	lowercase_			:  Tuple									= torch.cat(__SCREAMING_SNAKE_CASE       ,							dim=0	)

											return encoded_inputs






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=None       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											if task_inputs is None:
																	raise ValueError('''You have to specify the task_input. Found None.'''	)
											elif images is None:
																	raise ValueError('''You have to specify the image. Found None.'''	)

											if not all(task in ['''semantic''', '''instance''', '''panoptic'''] for task in task_inputs	):
																	raise ValueError('''task_inputs must be semantic, instance, or panoptic.'''	)

											lowercase_			:  Dict									= self.image_processor.encode_inputs(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)

											if isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	):
																	lowercase_			:  List[Any]									= [task_inputs]

											if isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	) and all(isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	) for task_input in task_inputs	):
																	lowercase_			:  int									= []
																	for task in task_inputs:
																							lowercase_			:  int									= F'''the task is {task}'''
																							task_token_inputs.append(__SCREAMING_SNAKE_CASE	)
																	lowercase_			:  str									= self._preprocess_text(__SCREAMING_SNAKE_CASE       ,							max_length=self.task_seq_length	)
											else:
																	raise TypeError('''Task Inputs should be a string or a list of strings.'''	)

											if hasattr(__SCREAMING_SNAKE_CASE       ,							'''text_inputs'''	):
																	lowercase_			:  Dict									= encoded_inputs.text_inputs

																	lowercase_			:  str									= []
																	for texts in texts_list:
																							lowercase_			:  List[str]									= self._preprocess_text(__SCREAMING_SNAKE_CASE       ,							max_length=self.max_seq_length	)
																							text_inputs.append(text_input_list.unsqueeze(0	)	)

																	lowercase_			:  Union[str, Any]									= torch.cat(__SCREAMING_SNAKE_CASE       ,							dim=0	)

											return encoded_inputs






					def 			_snake_case					(     self       ,							*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return self.image_processor.post_process_semantic_segmentation(*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return self.image_processor.post_process_instance_segmentation(*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)






					def 			_snake_case					(     self       ,							*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											return self.image_processor.post_process_panoptic_segmentation(*__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)



