





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


UpperCAmelCase__  :	str     =50_00_00

UpperCAmelCase__ ,UpperCAmelCase__  :	Dict     =os.path.split(__file__)
UpperCAmelCase__  :	str     =os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))





@get_duration
def    _lowercase    (  _UpperCAmelCase )  ->     List[Any]:
				lowerCamelCase		       =dataset.select(range(0	,					len(_UpperCAmelCase )	,					2 ) )





@get_duration
def    _lowercase    (  _UpperCAmelCase )  ->     Tuple:
				lowerCamelCase		       =dataset.sort("""numbers""" )





@get_duration
def    _lowercase    (  _UpperCAmelCase )  ->     Optional[int]:
				lowerCamelCase		       =dataset.shuffle()





@get_duration
def    _lowercase    (  _UpperCAmelCase )  ->     List[Any]:
				lowerCamelCase		       =dataset.train_test_split(0.1 )





@get_duration
def    _lowercase    (  _UpperCAmelCase	,					_UpperCAmelCase=10 )  ->     Optional[int]:
				for shard_id in range(_UpperCAmelCase ):
								lowerCamelCase		       =dataset.shard(_UpperCAmelCase	,					_UpperCAmelCase )





def    _lowercase    (  )  ->     Optional[int]:
				lowerCamelCase		       ={"""num examples""": SPEED_TEST_N_EXAMPLES}
				lowerCamelCase		       =(select, sort, shuffle, train_test_split, shard)
				with tempfile.TemporaryDirectory() as tmp_dir:
								print("""generating dataset""" )
								lowerCamelCase		       =datasets.Features({"""text""": datasets.Value("""string""" ), """numbers""": datasets.Value("""float32""" )} )
								lowerCamelCase		       =generate_example_dataset(
								    os.path.join(_UpperCAmelCase	,					"""dataset.arrow""" )	,					_UpperCAmelCase	,					num_examples=_UpperCAmelCase )
								print("""Functions""" )
								for func in functions:
												print(func.__name__ )
												lowerCamelCase		       =func(_UpperCAmelCase )

				with open(_UpperCAmelCase	,					"""wb""" ) as f:
								f.write(json.dumps(_UpperCAmelCase ).encode("""utf-8""" ) )


if __name__ == "__main__":  # useful to run the profiler
							benchmark_indices_mapping()











# 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 				__SCREAMING_SNAKE_CASE							(		lowerCamelCase  ):

					@classmethod
					def 	lowercase_							(				cls					):







						'''simple docstring'''




						return cls





					@slow
					@require_torch_gpu
					def 	lowercase_							(				self					):







						'''simple docstring'''




						lowerCamelCase_							:		Dict							   =							self.get_auto_remove_tmp_dir()
						lowerCamelCase_							:		Tuple							   =							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_							:		List[Any]							   =							get_gpu_count()
						lowerCamelCase_							:		Union[str, Any]							   =							f"\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        ".split()
						lowerCamelCase_							:		int							   =							[sys.executable] + distributed_args + args
						execute_subprocess_async(__lowercase ,       env=self.get_env()					)

						lowerCamelCase_							:		Any							   =							os.path.join(__lowercase ,       'test_bleu.json'					)
						lowerCamelCase_							:		List[Any]							   =							load_json(__lowercase					)
						# print(metrics)
						self.assertGreaterEqual(metrics['bleu'] ,       25					)
