




'''simple docstring'''

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 __magic_name__(						_UpperCamelCase      ):






						@classmethod
						def       __lowerCAmelCase(   cls						:						Union[str, Any]       ):



									'''simple docstring'''






									return cls







						@slow
						@require_torch_gpu
						def       __lowerCAmelCase(   self						:						int       ):



									'''simple docstring'''






									snake_case__          =						self.get_auto_remove_tmp_dir()
									snake_case__          =						f"""
            --model_name Helsinki-NLP/opus-mt-en-ro
            --save_dir {output_dir}
            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
            --num_beams 2
            --task translation
        """.split()

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

									snake_case__          =						os.path.join(a__					,   """test_bleu.json"""       )
									snake_case__          =						load_json(a__       )
									# print(metrics)
									self.assertGreaterEqual(metrics["""bleu"""]					,   2_5       )



"""simple docstring"""


from .hash_table import HashTable
class snake_case   (	_UpperCamelCase):







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





						'''simple docstring'''







						super().__init__(*a__     , **a__		)







		def 			a_			(       self   :							Tuple     , a__   :							int     , a__   :							str=None		)							->    Optional[int]:





						'''simple docstring'''







						_A       	=      1
						_A       	=      self.hash_function(key + i * i		)

						while self.values[new_key] is not None and self.values[new_key] != key:
										i += 1
										_A       	=      (
										    self.hash_function(key + i * i		)
										    if not self.balanced_factor() >= self.lim_charge
										    else None
										)

										if new_key is None:
														break

						return new_key