
'''simple docstring'''




import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


lowercase     :							Tuple       						=     50_00_00

lowercase						,	lowercase     :							List[Any]       						=     os.path.split(__file__)
lowercase     :							Union[str, Any]       						=     os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))







@get_duration
def 						lowerCAmelCase_							(  snake_case__						,							**snake_case__		):




    '''simple docstring'''



    A			:  Dict   =		dataset.map(**snake_case__		)







@get_duration
def 						lowerCAmelCase_							(  snake_case__						,							**snake_case__		):




    '''simple docstring'''



    A			:  Tuple   =		dataset.filter(**snake_case__		)







def 						lowerCAmelCase_							(  ):




    '''simple docstring'''



    A			:  str   =		{'''num examples''': SPEED_TEST_N_EXAMPLES}
    with tempfile.TemporaryDirectory() as tmp_dir:
        A			:  int   =		datasets.Features({'''text''': datasets.Value('''string'''		), '''numbers''': datasets.Value('''float32'''		)}		)
        A			:  Dict   =		generate_example_dataset(
            os.path.join(snake_case__						,							'''dataset.arrow'''		)						,							snake_case__						,							num_examples=snake_case__		)

        A			:  List[str]   =		transformers.AutoTokenizer.from_pretrained('''bert-base-cased'''						,							use_fast=snake_case__		)

        def tokenize(snake_case__		):
            return tokenizer(examples['''text''']		)

        A			:  str   =		map(snake_case__		)

        A			:  List[str]   =		map(snake_case__						,							batched=snake_case__		)

        A			:  Tuple   =		map(snake_case__						,							function=lambda snake_case__		: None						,							batched=snake_case__		)

        with dataset.formatted_as(type='''numpy'''		):
            A			:  Optional[Any]   =		map(snake_case__						,							function=lambda snake_case__		: None						,							batched=snake_case__		)

        with dataset.formatted_as(type='''pandas'''		):
            A			:  Optional[Any]   =		map(snake_case__						,							function=lambda snake_case__		: None						,							batched=snake_case__		)

        with dataset.formatted_as(type='''torch'''						,							columns='''numbers'''		):
            A			:  Optional[int]   =		map(snake_case__						,							function=lambda snake_case__		: None						,							batched=snake_case__		)

        with dataset.formatted_as(type='''tensorflow'''						,							columns='''numbers'''		):
            A			:  Union[str, Any]   =		map(snake_case__						,							function=lambda snake_case__		: None						,							batched=snake_case__		)

        A			:  Any   =		map(snake_case__						,							function=snake_case__						,							batched=snake_case__		)

        A			:  Any   =		filter(snake_case__		)

        # Activate later when tokenizer support batched inputs
        # with dataset.formatted_as(type='numpy'):
        #     times[func.__name__ + " fast-tokenizer batched numpy"] = func(dataset, function=tokenize, batched=True)

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


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






'''simple docstring'''




import random







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__		):




    '''simple docstring'''



    A			:  Optional[Any]   =		a[left_index]
    A			:  List[str]   =		left_index + 1
    for j in range(left_index + 1						,							snake_case__		):
        if a[j] < pivot:
            A,    A			:  Optional[int]   =		a[i], a[j]
            i += 1
    A,    A			:  str   =		a[i - 1], a[left_index]
    return i - 1







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__		):




    '''simple docstring'''



    if left < right:
        A			:  Optional[Any]   =		random.randint(snake_case__						,							right - 1		)
        A,    A			:  List[str]   =		(
            a[left],
            a[pivot],
        )  # switches the pivot with the left most bound
        A			:  Any   =		partition(snake_case__						,							snake_case__						,							snake_case__		)
        quick_sort_random(
            snake_case__						,							snake_case__						,							snake_case__		)  # recursive quicksort to the left of the pivot point
        quick_sort_random(
            snake_case__						,							pivot_index + 1						,							snake_case__		)  # recursive quicksort to the right of the pivot point







def 						lowerCAmelCase_							(  ):




    '''simple docstring'''



    A			:  Any   =		input('''Enter numbers separated by a comma:\n'''		).strip()
    A			:  List[str]   =		[int(snake_case__		) for item in user_input.split(''','''		)]

    quick_sort_random(snake_case__						,							0						,							len(snake_case__		)		)

    print(snake_case__		)


if __name__ == "__main__":
      main()




