



"""simple docstring"""







import enum
import warnings

from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_tf_available():
       import tensorflow as tf

       from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

if is_torch_available():
       from ..models.auto.modeling_auto import MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

lowerCAmelCase__									=logging.get_logger(__name__)




class        A__(  enum.Enum			):
      lowerCAmelCase										=				0
      lowerCAmelCase										=				1






@add_end_docstrings(__magic_name__			)
class        A__(  __magic_name__			):
      lowerCAmelCase										=				'''generated'''







      def __init__(					self		:     Any				,				*__SCREAMING_SNAKE_CASE		:     Tuple				,				**__SCREAMING_SNAKE_CASE		:     Tuple			)							->		str:






            """simple docstring"""

            super().__init__(*__SCREAMING_SNAKE_CASE				,				**__SCREAMING_SNAKE_CASE			)

            self.check_model_type(
                TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
                if self.framework == '''tf'''
                else MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING			)







      def  _a   (					self		:     Optional[int]				,				__SCREAMING_SNAKE_CASE		:     Any=None				,				__SCREAMING_SNAKE_CASE		:     Optional[Any]=None				,				__SCREAMING_SNAKE_CASE		:     Any=None				,				__SCREAMING_SNAKE_CASE		:     List[str]=None				,				__SCREAMING_SNAKE_CASE		:     Tuple=None				,				__SCREAMING_SNAKE_CASE		:     str=None				,				**__SCREAMING_SNAKE_CASE		:     List[Any]				,				)							->		str:






            """simple docstring"""

            __SCREAMING_SNAKE_CASE       		=   {}
            if truncation is not None:
                  __SCREAMING_SNAKE_CASE       		=   truncation

            __SCREAMING_SNAKE_CASE       		=   generate_kwargs

            __SCREAMING_SNAKE_CASE       		=   {}
            if return_tensors is not None and return_type is None:
                  __SCREAMING_SNAKE_CASE       		=   ReturnType.TENSORS if return_tensors else ReturnType.TEXT
            if return_type is not None:
                  __SCREAMING_SNAKE_CASE       		=   return_type

            if clean_up_tokenization_spaces is not None:
                  __SCREAMING_SNAKE_CASE       		=   clean_up_tokenization_spaces

            if stop_sequence is not None:
                  __SCREAMING_SNAKE_CASE       		=   self.tokenizer.encode(__SCREAMING_SNAKE_CASE				,				add_special_tokens=__SCREAMING_SNAKE_CASE			)
                  if len(__SCREAMING_SNAKE_CASE			) > 1:
                        warnings.warn(
                            '''Stopping on a multiple token sequence is not yet supported on transformers. The first token of'''
                            ''' the stop sequence will be used as the stop sequence string in the interim.'''			)
                  __SCREAMING_SNAKE_CASE       		=   stop_sequence_ids[0]

            return preprocess_params, forward_params, postprocess_params







      def  _a   (					self		:     Optional[int]				,				__SCREAMING_SNAKE_CASE		:     int				,				__SCREAMING_SNAKE_CASE		:     int				,				__SCREAMING_SNAKE_CASE		:     int			)							->		str:






            """simple docstring"""

            return True







      def  _a   (					self		:     Dict				,				*__SCREAMING_SNAKE_CASE		:     Optional[int]				,				__SCREAMING_SNAKE_CASE		:     List[str]			)							->		int:






            """simple docstring"""

            __SCREAMING_SNAKE_CASE       		=   self.model.config.prefix if self.model.config.prefix is not None else ''''''
            if isinstance(args[0]				,				__SCREAMING_SNAKE_CASE			):
                  if self.tokenizer.pad_token_id is None:
                        raise ValueError('''Please make sure that the tokenizer has a pad_token_id when using a batch input'''			)
                  __SCREAMING_SNAKE_CASE       		=   ([prefix + arg for arg in args[0]],)
                  __SCREAMING_SNAKE_CASE       		=   True

            elif isinstance(args[0]				,				__SCREAMING_SNAKE_CASE			):
                  __SCREAMING_SNAKE_CASE       		=   (prefix + args[0],)
                  __SCREAMING_SNAKE_CASE       		=   False
            else:
                  raise ValueError(
                      f""" `args[0]`: {args[0]} have the wrong format. The should be either of type `str` or type `list`"""			)
            __SCREAMING_SNAKE_CASE       		=   self.tokenizer(*__SCREAMING_SNAKE_CASE				,				padding=__SCREAMING_SNAKE_CASE				,				truncation=__SCREAMING_SNAKE_CASE				,				return_tensors=self.framework			)
            # This is produced by tokenizers but is an invalid generate kwargs
            if "token_type_ids" in inputs:
                  del inputs["token_type_ids"]
            return inputs







      def __call__(					self		:     Tuple				,				*__SCREAMING_SNAKE_CASE		:     Any				,				**__SCREAMING_SNAKE_CASE		:     str			)							->		Union[str, Any]:






            """simple docstring"""

            __SCREAMING_SNAKE_CASE       		=   super().__call__(*__SCREAMING_SNAKE_CASE				,				**__SCREAMING_SNAKE_CASE			)
            if (
                isinstance(args[0]				,				__SCREAMING_SNAKE_CASE			)
                and all(isinstance(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE			) for el in args[0]			)
                and all(len(__SCREAMING_SNAKE_CASE			) == 1 for res in result			)
            ):
                  return [res[0] for res in result]
            return result







      def  _a   (					self		:     Dict				,				__SCREAMING_SNAKE_CASE		:     Optional[Any]				,				__SCREAMING_SNAKE_CASE		:     List[str]=TruncationStrategy.DO_NOT_TRUNCATE				,				**__SCREAMING_SNAKE_CASE		:     Any			)							->		Optional[Any]:






            """simple docstring"""

            __SCREAMING_SNAKE_CASE       		=   self._parse_and_tokenize(__SCREAMING_SNAKE_CASE				,				truncation=__SCREAMING_SNAKE_CASE				,				**__SCREAMING_SNAKE_CASE			)
            return inputs







      def  _a   (					self		:     Any				,				__SCREAMING_SNAKE_CASE		:     int				,				**__SCREAMING_SNAKE_CASE		:     int			)							->		int:






            """simple docstring"""

            if self.framework == "pt":
                  __SCREAMING_SNAKE_CASE		,				__SCREAMING_SNAKE_CASE       		=   model_inputs['''input_ids'''].shape
            elif self.framework == "tf":
                  __SCREAMING_SNAKE_CASE		,				__SCREAMING_SNAKE_CASE       		=   tf.shape(model_inputs['''input_ids''']			).numpy()

            __SCREAMING_SNAKE_CASE       		=   generate_kwargs.get('''min_length'''				,				self.model.config.min_length			)
            __SCREAMING_SNAKE_CASE       		=   generate_kwargs.get('''max_length'''				,				self.model.config.max_length			)
            self.check_inputs(__SCREAMING_SNAKE_CASE				,				generate_kwargs['''min_length''']				,				generate_kwargs['''max_length''']			)
            __SCREAMING_SNAKE_CASE       		=   self.model.generate(**__SCREAMING_SNAKE_CASE				,				**__SCREAMING_SNAKE_CASE			)
            __SCREAMING_SNAKE_CASE       		=   output_ids.shape[0]
            if self.framework == "pt":
                  __SCREAMING_SNAKE_CASE       		=   output_ids.reshape(__SCREAMING_SNAKE_CASE				,				out_b // in_b				,				*output_ids.shape[1:]			)
            elif self.framework == "tf":
                  __SCREAMING_SNAKE_CASE       		=   tf.reshape(__SCREAMING_SNAKE_CASE				,				(in_b, out_b // in_b, *output_ids.shape[1:])			)
            return {"output_ids": output_ids}







      def  _a   (					self		:     Optional[int]				,				__SCREAMING_SNAKE_CASE		:     Dict				,				__SCREAMING_SNAKE_CASE		:     Any=ReturnType.TEXT				,				__SCREAMING_SNAKE_CASE		:     int=False			)							->		Any:






            """simple docstring"""

            __SCREAMING_SNAKE_CASE       		=   []
            for output_ids in model_outputs["output_ids"][0]:
                  if return_type == ReturnType.TENSORS:
                        __SCREAMING_SNAKE_CASE       		=   {f"""{self.return_name}_token_ids""": output_ids}
                  elif return_type == ReturnType.TEXT:
                        __SCREAMING_SNAKE_CASE       		=   {
                            f"""{self.return_name}_text""": self.tokenizer.decode(
                                __SCREAMING_SNAKE_CASE				,				skip_special_tokens=__SCREAMING_SNAKE_CASE				,				clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE				,				)
                        }
                  records.append(__SCREAMING_SNAKE_CASE			)
            return records






@add_end_docstrings(__magic_name__			)
class        A__(  __magic_name__			):
      lowerCAmelCase										=				'''summary'''







      def __call__(					self		:     Any				,				*__SCREAMING_SNAKE_CASE		:     List[str]				,				**__SCREAMING_SNAKE_CASE		:     Optional[int]			)							->		List[str]:






            """simple docstring"""

            return super().__call__(*__SCREAMING_SNAKE_CASE				,				**__SCREAMING_SNAKE_CASE			)







      def  _a   (					self		:     Any				,				__SCREAMING_SNAKE_CASE		:     int				,				__SCREAMING_SNAKE_CASE		:     int				,				__SCREAMING_SNAKE_CASE		:     int			)							->		List[Any]:






            """simple docstring"""

            if max_length < min_length:
                  logger.warning(f"""Your min_length={min_length} must be inferior than your max_length={max_length}."""			)

            if input_length < max_length:
                  logger.warning(
                      f"""Your max_length is set to {max_length}, but your input_length is only {input_length}. Since this is """
                      '''a summarization task, where outputs shorter than the input are typically wanted, you might '''
                      f"""consider decreasing max_length manually, e.g. summarizer(\'...\', max_length={input_length//2})"""			)






@add_end_docstrings(__magic_name__			)
class        A__(  __magic_name__			):
      lowerCAmelCase										=				'''translation'''







      def  _a   (					self		:     List[Any]				,				__SCREAMING_SNAKE_CASE		:     int				,				__SCREAMING_SNAKE_CASE		:     int				,				__SCREAMING_SNAKE_CASE		:     int			)							->		int:






            """simple docstring"""

            if input_length > 0.9 * max_length:
                  logger.warning(
                      f"""Your input_length: {input_length} is bigger than 0.9 * max_length: {max_length}. You might consider """
                      '''increasing your max_length manually, e.g. translator(\'...\', max_length=400)'''			)
            return True







      def  _a   (					self		:     str				,				*__SCREAMING_SNAKE_CASE		:     Union[str, Any]				,				__SCREAMING_SNAKE_CASE		:     Any=TruncationStrategy.DO_NOT_TRUNCATE				,				__SCREAMING_SNAKE_CASE		:     Optional[Any]=None				,				__SCREAMING_SNAKE_CASE		:     List[str]=None			)							->		Dict:






            """simple docstring"""

            if getattr(self.tokenizer				,				'''_build_translation_inputs'''				,				__SCREAMING_SNAKE_CASE			):
                  return self.tokenizer._build_translation_inputs(
                      *__SCREAMING_SNAKE_CASE				,				return_tensors=self.framework				,				truncation=__SCREAMING_SNAKE_CASE				,				src_lang=__SCREAMING_SNAKE_CASE				,				tgt_lang=__SCREAMING_SNAKE_CASE			)
            else:
                  return super()._parse_and_tokenize(*__SCREAMING_SNAKE_CASE				,				truncation=__SCREAMING_SNAKE_CASE			)







      def  _a   (					self		:     int				,				__SCREAMING_SNAKE_CASE		:     List[str]=None				,				__SCREAMING_SNAKE_CASE		:     Union[str, Any]=None				,				**__SCREAMING_SNAKE_CASE		:     Optional[int]			)							->		Any:






            """simple docstring"""

            __SCREAMING_SNAKE_CASE		,				__SCREAMING_SNAKE_CASE		,				__SCREAMING_SNAKE_CASE       		=   super()._sanitize_parameters(**__SCREAMING_SNAKE_CASE			)
            if src_lang is not None:
                  __SCREAMING_SNAKE_CASE       		=   src_lang
            if tgt_lang is not None:
                  __SCREAMING_SNAKE_CASE       		=   tgt_lang
            if src_lang is None and tgt_lang is None:
                  # Backward compatibility, direct arguments use is preferred.
                  __SCREAMING_SNAKE_CASE       		=   kwargs.get('''task'''				,				self.task			)
                  __SCREAMING_SNAKE_CASE       		=   task.split('''_'''			)
                  if task and len(__SCREAMING_SNAKE_CASE			) == 4:
                        # translation, XX, to YY
                        __SCREAMING_SNAKE_CASE       		=   items[1]
                        __SCREAMING_SNAKE_CASE       		=   items[3]
            return preprocess_params, forward_params, postprocess_params







      def __call__(					self		:     Optional[Any]				,				*__SCREAMING_SNAKE_CASE		:     Any				,				**__SCREAMING_SNAKE_CASE		:     str			)							->		Optional[Any]:






            """simple docstring"""

            return super().__call__(*__SCREAMING_SNAKE_CASE				,				**__SCREAMING_SNAKE_CASE			)






from __future__ import annotations

from random import random
from typing import Generic, TypeVar

__UpperCamelCase   :			Any          = TypeVar("KT")
__UpperCamelCase   :			List[Any]          = TypeVar("VT")

class 						__lowerCAmelCase      (      Generic[KT, VT]					):
							def __init__(		self		:Union[str, Any]						, __magic_name__		:KT | str = "root"						, __magic_name__		:VT | None = None							):







								'''simple docstring'''







								a									=				key
								a									=				value
								a									=				[]
							def __repr__(		self		:List[Any]							):







								'''simple docstring'''







								return F'Node({self.key}: {self.value})'





							@property
							def  lowerCamelCase__				(		self		:List[str]							):







								'''simple docstring'''







								return len(self.forward							)







class 						__lowerCAmelCase      (      Generic[KT, VT]					):
							def __init__(		self		:Optional[Any]						, __magic_name__		:float = 0.5						, __magic_name__		:int = 16							):







								'''simple docstring'''







								a									=				Node[KT, VT]()
								a									=				0
								a									=				p
								a									=				max_level
							def __str__(		self		:Tuple							):







								'''simple docstring'''







								a									=				list(self							)

								if len(__magic_name__							) == 0:
									return F'SkipList(level={self.level})'

								a									=				max((len(str(__magic_name__							)							) for item in items)						, default=4							)
								a									=				max(__magic_name__						, 4							) + 4

								a									=				self.head
								a									=				[]

								a									=				node.forward.copy()
								lines.append(F'[{node.key}]'.ljust(__magic_name__						, """-"""							) + """* """ * len(__magic_name__							)							)
								lines.append(""" """ * label_size + """| """ * len(__magic_name__							)							)

								while len(node.forward							) != 0:
									a									=				node.forward[0]

									lines.append(
									    F'[{node.key}]'.ljust(__magic_name__						, """-"""							)
									    + """ """.join(str(n.key							) if n.key == node.key else """|""" for n in forwards							)							)
									lines.append(""" """ * label_size + """| """ * len(__magic_name__							)							)
									a									=				node.forward

								lines.append("""None""".ljust(__magic_name__							) + """* """ * len(__magic_name__							)							)
								return F'SkipList(level={self.level})\n' + "\n".join(__magic_name__							)
							def __iter__(		self		:int							):







								'''simple docstring'''







								a									=				self.head

								while len(node.forward							) != 0:
									yield node.forward[0].key
									a									=				node.forward[0]
							def  lowerCamelCase__				(		self		:int							):







								'''simple docstring'''







								a									=				1
								while random() < self.p and level < self.max_level:
									level += 1

								return level
							def  lowerCamelCase__				(		self		:Dict						, __magic_name__		:int							):







								'''simple docstring'''







								a									=				[]

								a									=				self.head

								for i in reversed(range(self.level							)							):
									# i < node.level - When node level is lesser than `i` decrement `i`.
									# node.forward[i].key < key - Jumping to node with key value higher
									#                             or equal to searched key would result
									#                             in skipping searched key.
									while i < node.level and node.forward[i].key < key:
										a									=				node.forward[i]
									# Each leftmost node (relative to searched node) will potentially have to
									# be updated.
									update_vector.append(__magic_name__							)

								update_vector.reverse()  # Note that we were inserting values in reverse order.

								# len(node.forward) != 0 - If current node doesn't contain any further
								#                          references then searched key is not present.
								# node.forward[0].key == key - Next node key should be equal to search key
								#                              if key is present.
								if len(node.forward							) != 0 and node.forward[0].key == key:
									return node.forward[0], update_vector
								else:
									return None, update_vector
							def  lowerCamelCase__				(		self		:List[str]						, __magic_name__		:KT							):







								'''simple docstring'''







								a							,					a									=				self._locate_node(__magic_name__							)

								if node is not None:
									for i, update_node in enumerate(__magic_name__							):
										# Remove or replace all references to removed node.
										if update_node.level > i and update_node.forward[i].key == key:
											if node.level > i:
												a									=				node.forward[i]
											else:
												a									=				update_node.forward[:i]
							def  lowerCamelCase__				(		self		:List[str]						, __magic_name__		:KT						, __magic_name__		:VT							):







								'''simple docstring'''







								a							,					a									=				self._locate_node(__magic_name__							)
								if node is not None:
									a									=				value
								else:
									a									=				self.random_level()

									if level > self.level:
										# After level increase we have to add additional nodes to head.
										for _ in range(self.level - 1						, __magic_name__							):
											update_vector.append(self.head							)
										a									=				level

									a									=				Node(__magic_name__						, __magic_name__							)

									for i, update_node in enumerate(update_vector[:level]							):
										# Change references to pass through new node.
										if update_node.level > i:
											new_node.forward.append(update_node.forward[i]							)

										if update_node.level < i + 1:
											update_node.forward.append(__magic_name__							)
										else:
											a									=				new_node





							def  lowerCamelCase__				(		self		:Dict						, __magic_name__		:VT							):







								'''simple docstring'''







								a							,					a									=				self._locate_node(__magic_name__							)

								if node is not None:
									return node.value

								return None







def 						__A						(      ) ->			Tuple:
	a									=				SkipList()
	skip_list.insert("""Key1"""				,     3       )
	skip_list.insert("""Key2"""				,     12       )
	skip_list.insert("""Key3"""				,     41       )
	skip_list.insert("""Key4"""				,     -19       )

	a									=				skip_list.head
	a									=				{}
	while node.level != 0:
		a									=				node.forward[0]
		a									=				node.value

	assert len(__lowerCamelCase       ) == 4
	assert all_values["Key1"] == 3
	assert all_values["Key2"] == 12
	assert all_values["Key3"] == 41
	assert all_values["Key4"] == -19





def 						__A						(      ) ->			Tuple:
	a									=				SkipList()
	skip_list.insert("""Key1"""				,     10       )
	skip_list.insert("""Key1"""				,     12       )

	skip_list.insert("""Key5"""				,     7       )
	skip_list.insert("""Key7"""				,     10       )
	skip_list.insert("""Key10"""				,     5       )

	skip_list.insert("""Key7"""				,     7       )
	skip_list.insert("""Key5"""				,     5       )
	skip_list.insert("""Key10"""				,     10       )

	a									=				skip_list.head
	a									=				{}
	while node.level != 0:
		a									=				node.forward[0]
		a									=				node.value

	if len(__lowerCamelCase       ) != 4:
		print()
	assert len(__lowerCamelCase       ) == 4
	assert all_values["Key1"] == 12
	assert all_values["Key7"] == 7
	assert all_values["Key5"] == 5
	assert all_values["Key10"] == 10





def 						__A						(      ) ->			Optional[int]:
	a									=				SkipList()
	assert skip_list.find("""Some key"""       ) is None





def 						__A						(      ) ->			Optional[int]:
	a									=				SkipList()

	skip_list.insert("""Key2"""				,     20       )
	assert skip_list.find("""Key2"""       ) == 20

	skip_list.insert("""Some Key"""				,     10       )
	skip_list.insert("""Key2"""				,     8       )
	skip_list.insert("""V"""				,     13       )

	assert skip_list.find("""Y"""       ) is None
	assert skip_list.find("""Key2"""       ) == 8
	assert skip_list.find("""Some Key"""       ) == 10
	assert skip_list.find("""V"""       ) == 13





def 						__A						(      ) ->			str:
	a									=				SkipList()
	skip_list.delete("""Some key"""       )

	assert len(skip_list.head.forward       ) == 0





def 						__A						(      ) ->			int:
	a									=				SkipList()

	skip_list.insert("""Key1"""				,     12       )
	skip_list.insert("""V"""				,     13       )
	skip_list.insert("""X"""				,     14       )
	skip_list.insert("""Key2"""				,     15       )

	skip_list.delete("""V"""       )
	skip_list.delete("""Key2"""       )

	assert skip_list.find("""V"""       ) is None
	assert skip_list.find("""Key2"""       ) is None





def 						__A						(      ) ->			Union[str, Any]:
	a									=				SkipList()

	skip_list.insert("""Key1"""				,     12       )
	skip_list.insert("""V"""				,     13       )
	skip_list.insert("""X"""				,     14       )
	skip_list.insert("""Key2"""				,     15       )

	skip_list.delete("""V"""       )
	assert skip_list.find("""V"""       ) is None
	assert skip_list.find("""X"""       ) == 14
	assert skip_list.find("""Key1"""       ) == 12
	assert skip_list.find("""Key2"""       ) == 15

	skip_list.delete("""X"""       )
	assert skip_list.find("""V"""       ) is None
	assert skip_list.find("""X"""       ) is None
	assert skip_list.find("""Key1"""       ) == 12
	assert skip_list.find("""Key2"""       ) == 15

	skip_list.delete("""Key1"""       )
	assert skip_list.find("""V"""       ) is None
	assert skip_list.find("""X"""       ) is None
	assert skip_list.find("""Key1"""       ) is None
	assert skip_list.find("""Key2"""       ) == 15

	skip_list.delete("""Key2"""       )
	assert skip_list.find("""V"""       ) is None
	assert skip_list.find("""X"""       ) is None
	assert skip_list.find("""Key1"""       ) is None
	assert skip_list.find("""Key2"""       ) is None





def 						__A						(      ) ->			Dict:
	a									=				SkipList()

	skip_list.insert("""Key1"""				,     12       )
	skip_list.insert("""V"""				,     13       )
	skip_list.insert("""X"""				,     142       )
	skip_list.insert("""Key2"""				,     15       )

	skip_list.delete("""X"""       )

	def traverse_keys(__lowerCamelCase       ):
		yield node.key
		for forward_node in node.forward:
			yield from traverse_keys(__lowerCamelCase       )

	assert len(set(traverse_keys(skip_list.head       )       )       ) == 4





def 						__A						(      ) ->			Optional[Any]:
	def is_sorted(__lowerCamelCase       ):
		return all(next_item >= item for item, next_item in zip(__lowerCamelCase				,     lst[1:]       )       )

	a									=				SkipList()
	for i in range(10       ):
		skip_list.insert(__lowerCamelCase				,     __lowerCamelCase       )
	assert is_sorted(list(__lowerCamelCase       )       )
	skip_list.delete(5       )
	skip_list.delete(8       )
	skip_list.delete(2       )
	assert is_sorted(list(__lowerCamelCase       )       )
	skip_list.insert(-12				,     -12       )
	skip_list.insert(77				,     77       )
	assert is_sorted(list(__lowerCamelCase       )       )





def 						__A						(      ) ->			Optional[Any]:
	for _ in range(100       ):
		# Repeat test 100 times due to the probabilistic nature of skip list
		# random values == random bugs
		test_insert()
		test_insert_overrides_existing_value()

		test_searching_empty_list_returns_none()
		test_search()

		test_deleting_item_from_empty_list_do_nothing()
		test_deleted_items_are_not_founded_by_find_method()
		test_delete_removes_only_given_key()
		test_delete_doesnt_leave_dead_nodes()

		test_iter_always_yields_sorted_values()





def 						__A						(      ) ->			Optional[int]:
	a									=				SkipList()
	skip_list.insert(2				,     """2"""       )
	skip_list.insert(4				,     """4"""       )
	skip_list.insert(6				,     """4"""       )
	skip_list.insert(4				,     """5"""       )
	skip_list.insert(8				,     """4"""       )
	skip_list.insert(9				,     """4"""       )

	skip_list.delete(4       )

	print(__lowerCamelCase       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()

