import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


__lowercase							 =					5_0000
__lowercase							 =					5000

__lowercase ,       __lowercase							 =					os.path.split(__file__)
__lowercase							 =					os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))



@get_duration
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    for i in range(SCREAMING_SNAKE_CASE	):
        __UpperCamelCase     :int			  =		dataset[i]



@get_duration
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    for i in range(0  ,			len(SCREAMING_SNAKE_CASE	)  ,			SCREAMING_SNAKE_CASE	):
        __UpperCamelCase     :str			  =		dataset[i : i + batch_size]



@get_duration
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    with dataset.formatted_as(type=SCREAMING_SNAKE_CASE	):
        for i in range(SCREAMING_SNAKE_CASE	):
            __UpperCamelCase     :List[str]			  =		dataset[i]



@get_duration
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    with dataset.formatted_as(type=SCREAMING_SNAKE_CASE	):
        for i in range(0  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
            __UpperCamelCase     :List[Any]			  =		dataset[i : i + batch_size]



def lowerCamelCase  (   ):
    '''simple docstring'''







    __UpperCamelCase     :Optional[Any]			  =		{'''num examples''': SPEED_TEST_N_EXAMPLES}
    __UpperCamelCase     :Optional[Any]			  =		[
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_000}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''pandas''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''torch''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''tensorflow''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 10}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1_000}),
    ]

    __UpperCamelCase     :List[str]			  =		[
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_000}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 10}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1_000}),
    ]
    with tempfile.TemporaryDirectory() as tmp_dir:
        print('''generating dataset'''	)
        __UpperCamelCase     :Any			  =		datasets.Features(
            {'''list''': datasets.Sequence(datasets.Value('''float32'''	)	), '''numbers''': datasets.Value('''float32'''	)}	)
        __UpperCamelCase     :int			  =		generate_example_dataset(
            os.path.join(SCREAMING_SNAKE_CASE  ,			'''dataset.arrow'''	)  ,			SCREAMING_SNAKE_CASE  ,			num_examples=SCREAMING_SNAKE_CASE  ,			seq_shapes={'''list''': (100,)}  ,			)
        print('''first set of iterations'''	)
        for func, kwargs in functions:
            print(func.__name__  ,			str(SCREAMING_SNAKE_CASE	)	)
            __UpperCamelCase     :Union[str, Any]			  =		func(SCREAMING_SNAKE_CASE  ,			**SCREAMING_SNAKE_CASE	)

        print('''shuffling dataset'''	)
        __UpperCamelCase     :Union[str, Any]			  =		dataset.shuffle()
        print('''Second set of iterations (after shuffling'''	)
        for func, kwargs in functions_shuffled:
            print('''shuffled '''  ,			func.__name__  ,			str(SCREAMING_SNAKE_CASE	)	)
            __UpperCamelCase     :List[Any]			  =		func(
                SCREAMING_SNAKE_CASE  ,			**SCREAMING_SNAKE_CASE	)

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


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






import random



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







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



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







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



def lowerCamelCase  (   ):
    '''simple docstring'''







    __UpperCamelCase     :Tuple			  =		input('''Enter numbers separated by a comma:\n'''	).strip()
    __UpperCamelCase     :Union[str, Any]			  =		[int(SCREAMING_SNAKE_CASE	) for item in user_input.split(''','''	)]

    quick_sort_random(SCREAMING_SNAKE_CASE  ,			0  ,			len(SCREAMING_SNAKE_CASE	)	)

    print(SCREAMING_SNAKE_CASE	)


if __name__ == "__main__":
    main()





