
"""simple docstring"""





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_a														=		5_0000
_a														=		5000

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



@get_duration
def       lowerCamelCase__		(			__snake_case,     __snake_case	)							->		Dict:


					"""simple docstring"""





					for i in range(__snake_case	):
										_UpperCamelCase							 =  dataset[i]



@get_duration
def       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case	)							->		str:


					"""simple docstring"""





					for i in range(0,     len(__snake_case	),     __snake_case	):
										_UpperCamelCase							 =  dataset[i : i + batch_size]



@get_duration
def       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case	)							->		Any:


					"""simple docstring"""





					with dataset.formatted_as(type=__snake_case	):
										for i in range(__snake_case	):
															_UpperCamelCase							 =  dataset[i]



@get_duration
def       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case,     __snake_case	)							->		Dict:


					"""simple docstring"""





					with dataset.formatted_as(type=__snake_case	):
										for i in range(0,     __snake_case,     __snake_case	):
															_UpperCamelCase							 =  dataset[i : i + batch_size]



def       lowerCamelCase__		(			)							->		str:


					"""simple docstring"""





					_UpperCamelCase							 =  {'''num examples''': SPEED_TEST_N_EXAMPLES}
					_UpperCamelCase							 =  [
					    (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}),
					]

					_UpperCamelCase							 =  [
					    (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'''	)
										_UpperCamelCase							 =  datasets.Features(
										    {'''list''': datasets.Sequence(datasets.Value('''float32'''	)	), '''numbers''': datasets.Value('''float32'''	)}	)
										_UpperCamelCase							 =  generate_example_dataset(
										    os.path.join(__snake_case,     '''dataset.arrow'''	),     __snake_case,     num_examples=__snake_case,     seq_shapes={'''list''': (1_00,)},     )
										print('''first set of iterations'''	)
										for func, kwargs in functions:
															print(func.__name__,     str(__snake_case	)	)
															_UpperCamelCase							 =  func(__snake_case,     **__snake_case	)

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








"""simple docstring"""





from __future__ import annotations



def       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case	)							->		int | float:


					"""simple docstring"""





					if len(__snake_case	) == 0:
										raise ValueError('''find_max() arg is an empty sequence'''	)
					if (
					    left >= len(__snake_case	)
					    or left < -len(__snake_case	)
					    or right >= len(__snake_case	)
					    or right < -len(__snake_case	)
					):
										raise IndexError('''list index out of range'''	)
					if left == right:
										return nums[left]
					_UpperCamelCase							 =  (left + right) >> 1  # the middle
					_UpperCamelCase							 =  find_max(__snake_case,     __snake_case,     __snake_case	)  # find max in range[left, mid]
					_UpperCamelCase							 =  find_max(__snake_case,     mid + 1,     __snake_case	)  # find max in range[mid + 1, right]

					return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
				import doctest

				doctest.testmod(verbose=True)






