import json
import os
import tempfile

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import ArrayaD
from utils import generate_examples, get_duration


lowercase__    :       int						=			(3_0, 4_8_7)
lowercase__    :       int						=			(3_6, 1_0_2_4)
lowercase__    :       Optional[int]						=			(1_0_0, 1_0_0)
lowercase__    :       Optional[Any]						=			1_0_0

lowercase__    :       Any						=			datasets.Features(
    {'''text''': ArrayaD(SHAPE_TEST_1, dtype='''float32'''), '''image''': ArrayaD(SHAPE_TEST_2, dtype='''float32''')}
)

lowercase__			,					lowercase__    :       int						=			os.path.split(__file__)
lowercase__    :       Optional[int]						=			os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			List[str]:
							with ArrowWriter(features=snake_case__     ,						path=os.path.join(snake_case__     ,						'''beta.arrow'''							)							) as writer:
														for key, record in dummy_data:
																					lowerCAmelCase				=	my_features.encode_example(snake_case__							)
																					writer.write(snake_case__							)
														lowerCAmelCase				=	writer.finalize()

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			int:
							lowerCAmelCase				=	datasets.Dataset.from_file(
							    filename=os.path.join(snake_case__     ,						'''beta.arrow'''							)     ,						info=datasets.DatasetInfo(features=snake_case__							)							)
							for _ in dataset:
														pass

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			Dict:
							lowerCAmelCase				=	datasets.Dataset.from_file(
							    filename=os.path.join(snake_case__     ,						'''beta.arrow'''							)     ,						info=datasets.DatasetInfo(features=snake_case__							)							)
							dataset.set_format('''numpy'''							)
							for _ in dataset:
														pass

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			Optional[Any]:
							lowerCAmelCase				=	1_0
							lowerCAmelCase				=	datasets.Dataset.from_file(
							    filename=os.path.join(snake_case__     ,						'''beta.arrow'''							)     ,						info=datasets.DatasetInfo(features=snake_case__							)							)
							for i in range(0     ,						len(snake_case__							)     ,						snake_case__							):
														lowerCAmelCase				=	dataset[i : i + batch_size]

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			Tuple:
							lowerCAmelCase				=	1_0
							lowerCAmelCase				=	datasets.Dataset.from_file(
							    filename=os.path.join(snake_case__     ,						'''beta.arrow'''							)     ,						info=datasets.DatasetInfo(features=snake_case__							)							)
							dataset.set_format('''numpy'''							)
							for i in range(0     ,						len(snake_case__							)     ,						snake_case__							):
														lowerCAmelCase				=	dataset[i : i + batch_size]

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			Dict:
							lowerCAmelCase				=	datasets.Dataset.from_file(
							    filename=os.path.join(snake_case__     ,						'''beta.arrow'''							)     ,						info=datasets.DatasetInfo(features=snake_case__							)							)
							for col in feats:
														lowerCAmelCase				=	dataset[col]

@get_duration
def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			Tuple:
							lowerCAmelCase				=	datasets.Dataset.from_file(
							    filename=os.path.join(snake_case__     ,						'''beta.arrow'''							)     ,						info=datasets.DatasetInfo(features=snake_case__							)							)
							dataset.set_format('''numpy'''							)
							for col in feats:
														lowerCAmelCase				=	dataset[col]

def      SCREAMING_SNAKE_CASE_  (		)  ->			Optional[Any]:
							lowerCAmelCase				=	{}
							lowerCAmelCase				=	(
							    read_unformated,
							    read_formatted_as_numpy,
							    read_batch_unformated,
							    read_batch_formatted_as_numpy,
							    read_col_unformated,
							    read_col_formatted_as_numpy,
							)
							with tempfile.TemporaryDirectory() as tmp_dir:
														lowerCAmelCase				=	datasets.Features({'''image''': ArrayaD(snake_case__     ,						dtype='''float32'''							)}							)
														lowerCAmelCase				=	generate_examples(features=snake_case__     ,						num_examples=snake_case__							)
														lowerCAmelCase				=	write(snake_case__     ,						snake_case__     ,						snake_case__							)
														for read_func in read_functions:
																					lowerCAmelCase				=	read_func(snake_case__     ,						snake_case__							)

							with tempfile.TemporaryDirectory() as tmp_dir:
														# don't use fixed length for fair comparison
														# feats = datasets.Features(
														#     {"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), SPEED_TEST_SHAPE[1]), SPEED_TEST_SHAPE[0])}
														# )
														lowerCAmelCase				=	datasets.Features({'''image''': datasets.Sequence(datasets.Sequence(datasets.Value('''float32'''							)							)							)}							)
														lowerCAmelCase				=	generate_examples(
														    features=snake_case__     ,						num_examples=snake_case__     ,						seq_shapes={'''image''': SPEED_TEST_SHAPE}							)
														lowerCAmelCase				=	write(snake_case__     ,						snake_case__     ,						snake_case__							)
														for read_func in read_functions:
																					lowerCAmelCase				=	read_func(snake_case__     ,						snake_case__							)

							with tempfile.TemporaryDirectory() as tmp_dir:
														# don't use fixed length for fair comparison
														# feats = datasets.Features(
														#     {"image": datasets.Sequence(datasets.Value("float32"), SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1])}
														# )
														lowerCAmelCase				=	datasets.Features({'''image''': datasets.Sequence(datasets.Value('''float32'''							)							)}							)
														lowerCAmelCase				=	generate_examples(
														    features=snake_case__     ,						num_examples=snake_case__     ,						seq_shapes={'''image''': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}     ,						)
														lowerCAmelCase				=	write(snake_case__     ,						snake_case__     ,						snake_case__							)
														for read_func in read_functions:
																					lowerCAmelCase				=	read_func(snake_case__     ,						snake_case__							)

							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_array_xd()




import math

def      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			float:
							lowerCAmelCase				=	math.log(2     ,						1_0							) * number
							lowerCAmelCase				=	round((log_number - int(snake_case__							))     ,						1_5							)

							return difference

def      SCREAMING_SNAKE_CASE_  (		snake_case__ = 6_7_8_9_1_0							)  ->			int:
							lowerCAmelCase				=	9_0
							lowerCAmelCase				=	0

							lowerCAmelCase				=	math.log(1.23     ,						1_0							)
							lowerCAmelCase				=	math.log(1.24     ,						1_0							)
							lowerCAmelCase				=	0

							while position < number:
														lowerCAmelCase				=	log_difference(snake_case__							)

														if difference >= upper_limit:
																					power_iterator += 9_3

														elif difference < lower_limit:
																					power_iterator += 1_9_6

														else:
																					lowerCAmelCase				=	power_iterator
																					power_iterator += 1_9_6
																					position += 1

							return previous_power


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	print(f'{solution() = }')



