


import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_snake_case	=							5_0000
_snake_case	=							5000

_snake_case,						_snake_case	=							os.path.split(__file__)
_snake_case	=							os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))
@get_duration
def       _a			(				SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		for i in range(SCREAMING_SNAKE_CASE					):
				lowercase__						=				dataset[i]
@get_duration
def       _a			(				SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		for i in range(0						,    len(SCREAMING_SNAKE_CASE					)						,    SCREAMING_SNAKE_CASE					):
				lowercase__						=				dataset[i : i + batch_size]
@get_duration
def       _a			(				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					):
						lowercase__						=				dataset[i]
@get_duration
def       _a			(				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					):
						lowercase__						=				dataset[i : i + batch_size]
def       _a			(				):


		"""simple docstring"""




		lowercase__						=				{'''num examples''': SPEED_TEST_N_EXAMPLES}
		lowercase__						=				[
		    (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''': 1_00}),
		    (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10_00}),
		    (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''': 10_00}),
		]

		lowercase__						=				[
		    (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''': 1_00}),
		    (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10_00}),
		    (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''': 10_00}),
		]
		with tempfile.TemporaryDirectory() as tmp_dir:
				print('''generating dataset'''					)
				lowercase__						=				datasets.Features(
				    {'''list''': datasets.Sequence(datasets.Value('''float32'''					)					), '''numbers''': datasets.Value('''float32'''					)}					)
				lowercase__						=				generate_example_dataset(
				    os.path.join(SCREAMING_SNAKE_CASE						,    '''dataset.arrow'''					)						,    SCREAMING_SNAKE_CASE						,    num_examples=SCREAMING_SNAKE_CASE						,    seq_shapes={'''list''': (1_00,)}						,    )
				print('''first set of iterations'''					)
				for func, kwargs in functions:
						print(func.__name__						,    str(SCREAMING_SNAKE_CASE					)					)
						lowercase__						=				func(SCREAMING_SNAKE_CASE						,    **SCREAMING_SNAKE_CASE					)

				print('''shuffling dataset'''					)
				lowercase__						=				dataset.shuffle()
				print('''Second set of iterations (after shuffling'''					)
				for func, kwargs in functions_shuffled:
						print('''shuffled '''						,    func.__name__						,    str(SCREAMING_SNAKE_CASE					)					)
						lowercase__						=				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()






def       _a			(				SCREAMING_SNAKE_CASE = 10_00					):


		"""simple docstring"""




		return sum(e for e in range(3						,    SCREAMING_SNAKE_CASE					) if e % 3 == 0 or e % 5 == 0					)


if __name__ == "__main__":
			print(f"""{solution() = }""")


