'''simple docstring'''




import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_lowercase		:					Any													=		500000

_lowercase							,			_lowercase		:					Optional[int]													=		os.path.split(__file__)
_lowercase		:					Union[str, Any]													=		os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))




@get_duration
def 				lowerCamelCase      ( UpperCAmelCase__			:   datasets.Dataset					)     -> Dict:
							lowercase_   :     str									=			dataset.select(range(0 , len(UpperCAmelCase__					) , 2					)					)




@get_duration
def 				lowerCamelCase      ( UpperCAmelCase__			:   datasets.Dataset					)     -> Optional[Any]:
							lowercase_   :     Optional[Any]									=			dataset.sort("""numbers"""					)




@get_duration
def 				lowerCamelCase      ( UpperCAmelCase__			:   datasets.Dataset					)     -> List[Any]:
							lowercase_   :     Dict									=			dataset.shuffle()




@get_duration
def 				lowerCamelCase      ( UpperCAmelCase__			:   datasets.Dataset					)     -> Dict:
							lowercase_   :     Optional[Any]									=			dataset.train_test_split(0.1					)




@get_duration
def 				lowerCamelCase      ( UpperCAmelCase__			:   datasets.Dataset , UpperCAmelCase__			:   Optional[Any]=10					)     -> Optional[int]:
							for shard_id in range(UpperCAmelCase__					):
														lowercase_   :     Any									=			dataset.shard(UpperCAmelCase__ , UpperCAmelCase__					)




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






'''simple docstring'''




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments




def 				lowerCamelCase      ( )     -> List[Any]:
							lowercase_   :     Tuple									=			HfArgumentParser(UpperCAmelCase__					)
							try:
														lowercase_   :     List[Any]									=			parser.parse_args_into_dataclasses()[0]
							except ValueError as e:
														lowercase_   :     int									=			"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
														lowercase_   :     Any									=			""" """.join(str(UpperCAmelCase__					).split(""" """					)[:-1]					)
														lowercase_   :     Optional[Any]									=			""""""
														lowercase_   :     List[str]									=			eval(str(UpperCAmelCase__					).split(""" """					)[-1]					)
														lowercase_   :     Dict									=			[]
														for arg in depreciated_args:
																					# arg[2:] removes '--'
																					if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																												# arg[5:] removes '--no_'
																												full_error_msg += arg_error_msg.format(arg[5:]					)
																					else:
																												wrong_args.append(UpperCAmelCase__					)
														if len(UpperCAmelCase__					) > 0:
																					lowercase_   :     Dict									=			full_error_msg + begin_error_msg + str(UpperCAmelCase__					)
														raise ValueError(UpperCAmelCase__					)

							lowercase_   :     Optional[int]									=			PyTorchBenchmark(args=UpperCAmelCase__					)
							benchmark.run()


if __name__ == "__main__":
						main()





