


'''simple docstring'''






from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

__UpperCAmelCase       							=				(3, 9, -11, 0, 7, 5, 1, -1)
__UpperCAmelCase       							=				(4, 6, 2, 0, 8, 10, 3, -2)




@dataclass
class 						a__							:





							'''simple docstring'''






							lowercase__     :  int
							lowercase__     :  Node | None




class 						a__							:





							'''simple docstring'''






							def __init__(						self   ,       lowerCamelCase_  )			->				None:
														lowerCAmelCase__			  =      None
														for i in sorted(lowerCamelCase_   ,       reverse=lowerCamelCase_  ):
																					lowerCAmelCase__			  =      Node(lowerCamelCase_   ,       self.head  )







							def __iter__(						self  )			->				Iterator[int]:
														lowerCAmelCase__			  =      self.head
														while node:
																					yield node.data
																					lowerCAmelCase__			  =      node.next_node







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







							def __str__(						self  )			->				str:
														return " -> ".join([str(lowerCamelCase_  ) for node in self]  )


def    _snake_case  (	A					,       A			)		->       SortedLinkedList:
							return SortedLinkedList(list(A			) + list(A			)			)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		__UpperCAmelCase       							=				SortedLinkedList
		print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))



'''simple docstring'''






import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


__UpperCAmelCase       							=				logging.getLogger(__name__)




@dataclass
@add_start_docstrings(TrainingArguments.__doc__    )
class 						a__							(				a__    ):





							'''simple docstring'''






							lowercase__     :  bool      		= field(default=a__							,							metadata={"help": "Whether to use SortishSampler or not."}    )
							lowercase__     :  bool      		= field(
							    default=a__							,							metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}    )
							lowercase__     :  Optional[int]      		= field(
							    default=a__							,							metadata={
							        "help": (
							            "The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default "
							            "to the `max_length` value of the model configuration."
							        )
							    }							,							)
							lowercase__     :  Optional[int]      		= field(
							    default=a__							,							metadata={
							        "help": (
							            "The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default "
							            "to the `num_beams` value of the model configuration."
							        )
							    }							,							)
							lowercase__     :  Optional[Union[str, Path, GenerationConfig]]      		= field(
							    default=a__							,							metadata={
							        "help": "Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."
							    }							,							)







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Dict:
														lowerCAmelCase__			  =      super().to_dict()
														for k, v in d.items():
																					if isinstance(lowerCamelCase_   ,       lowerCamelCase_  ):
																												lowerCAmelCase__			  =      v.to_dict()
														return d