



import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


snake_case     :    str						=    5_0_0_0_0_0

snake_case			,							snake_case     :    Optional[int]						=    os.path.split(__file__)
snake_case     :    List[Any]						=    os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))
@get_duration
def 						snake_case__							(       __lowercase							)		->		str:







						"""simple docstring"""

						A__						:				List[Any]         =			dataset.select(range(0				,  len(__lowercase							)				,  2							)							)
@get_duration
def 						snake_case__							(       __lowercase							)		->		str:







						"""simple docstring"""

						A__						:				List[str]         =			dataset.sort("numbers"							)
@get_duration
def 						snake_case__							(       __lowercase							)		->		Optional[int]:







						"""simple docstring"""

						A__						:				List[str]         =			dataset.shuffle()
@get_duration
def 						snake_case__							(       __lowercase							)		->		Union[str, Any]:







						"""simple docstring"""

						A__						:				Optional[Any]         =			dataset.train_test_split(0.1							)
@get_duration
def 						snake_case__							(       __lowercase				,  __lowercase=1_0							)		->		Any:







						"""simple docstring"""

						for shard_id in range(__lowercase							):
												A__						:				Any         =			dataset.shard(__lowercase				,  __lowercase							)
def 						snake_case__							(       )		->		List[Any]:







						"""simple docstring"""

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

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


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




def 						snake_case__							(       __lowercase							)		->		int:







						"""simple docstring"""

						A__						:				Any         =			0
						for plain_chr in plain_text:
												A__						:				List[str]         =			(
												    ord(__lowercase							) + (hash_value << 6) + (hash_value << 1_6) - hash_value
												)
						return hash_value