from __future__ import annotations

from collections.abc import Iterator
from typing import Any




class        lowercase_  :



	"""simple docstring"""





	def __init__(							self		,      __SCREAMING_SNAKE_CASE    )						->None:
								lowerCAmelCase     		=		data
								lowerCAmelCase     		=		None




	def __str__(							self    )						->str:
								return F"{self.data}"




class        lowercase_  :



	"""simple docstring"""





	def __init__(							self    )						->None:
								lowerCAmelCase     		=		None
								lowerCAmelCase     		=		None


	def __iter__(							self    )						->Iterator[Any]:
								lowerCAmelCase     		=		self.front
								while node:
															yield node.data
															lowerCAmelCase     		=		node.next


	def __len__(							self    )						->int:
								return len(tuple(iter(self    )    )    )


	def __str__(							self    )						->str:
								return " <- ".join(str(__SCREAMING_SNAKE_CASE    ) for item in self    )


	def       SCREAMING_SNAKE_CASE_    (							self    )						->bool:
								return len(self    ) == 0


	def       SCREAMING_SNAKE_CASE_    (							self		,      __SCREAMING_SNAKE_CASE    )						->None:
								lowerCAmelCase     		=		Node(__SCREAMING_SNAKE_CASE    )
								if self.is_empty():
															lowerCAmelCase     		=		lowerCAmelCase     		=		node
								else:
															assert isinstance(self.rear		,      __SCREAMING_SNAKE_CASE    )
															lowerCAmelCase     		=		node
															lowerCAmelCase     		=		node


	def       SCREAMING_SNAKE_CASE_    (							self    )						->Any:
								if self.is_empty():
															raise IndexError('''dequeue from empty queue'''    )
								assert isinstance(self.front		,      __SCREAMING_SNAKE_CASE    )
								lowerCAmelCase     		=		self.front
								lowerCAmelCase     		=		self.front.next
								if self.front is None:
															lowerCAmelCase     		=		None
								return node.data




	def       SCREAMING_SNAKE_CASE_    (							self    )						->None:
								lowerCAmelCase     		=		lowerCAmelCase     		=		None


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

	testmod()




# as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.

import os
import sys

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow

from .utils import load_json




class        lowercase_  (  UpperCamelCase_						):



	"""simple docstring"""





	@classmethod
	def       SCREAMING_SNAKE_CASE_    (							cls    )						->Union[str, Any]:
								return cls




	@slow
	@require_torch_gpu
	def       SCREAMING_SNAKE_CASE_    (							self    )						->int:
								lowerCAmelCase     		=		self.get_auto_remove_tmp_dir()
								lowerCAmelCase     		=		F"\n            --model_name Helsinki-NLP/opus-mt-en-ro\n            --save_dir {output_dir}\n            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro\n            --num_beams 2\n            --task translation\n        ".split()

								# we want this test to run even if there is only one GPU, but if there are more we use them all
								lowerCAmelCase     		=		get_gpu_count()
								lowerCAmelCase     		=		F"\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        ".split()
								lowerCAmelCase     		=		[sys.executable] + distributed_args + args
								execute_subprocess_async(__SCREAMING_SNAKE_CASE		,      env=self.get_env()    )

								lowerCAmelCase     		=		os.path.join(__SCREAMING_SNAKE_CASE		,      '''test_bleu.json'''    )
								lowerCAmelCase     		=		load_json(__SCREAMING_SNAKE_CASE    )
								# print(metrics)
								self.assertGreaterEqual(metrics['''bleu''']		,      25    )



