






import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


__A					=	5_00_00
__A					=	50_00

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







@get_duration
def       lowercase__	(					A_:						Dict  ,      A_:						Union[str, Any]		)	->				Optional[Any]:







       """simple docstring"""






       for i in range(snake_case__		):
              __UpperCAmelCase     				=dataset[i]







@get_duration
def       lowercase__	(					A_:						Optional[Any]  ,      A_:						str  ,      A_:						List[Any]		)	->				Optional[Any]:







       """simple docstring"""






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







@get_duration
def       lowercase__	(					A_:						Tuple  ,      A_:						Optional[Any]  ,      A_:						List[Any]		)	->				Dict:







       """simple docstring"""






       with dataset.formatted_as(type=snake_case__		):
              for i in range(snake_case__		):
                     __UpperCAmelCase     				=dataset[i]







@get_duration
def       lowercase__	(					A_:						Tuple  ,      A_:						List[Any]  ,      A_:						Any  ,      A_:						Optional[Any]		)	->				Union[str, Any]:







       """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       lowercase__	(					)	->				Optional[Any]:







       """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""": 100}),
           (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 1000}),
           (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""": 1000}),
       ]

       __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""": 100}),
           (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 1000}),
           (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""": 1000}),
       ]
       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""": (100,)}  ,      )
              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       __UpperCamelCase						(		snake_case__ , snake_case__ = None , snake_case__ = None       ):
	if start is None:
		A_		:    Dict						     = 0

	if end is None:
		A_		:    Dict						     = len(snake_case__       ) - 1

	if start >= end:
		return

	A_		:    List[Any]						     = (start + end) // 2

	slowsort(snake_case__ , snake_case__ , snake_case__       )
	slowsort(snake_case__ , mid + 1 , snake_case__       )

	if sequence[end] < sequence[mid]:
		A_     ,  A_		:    Dict						     = sequence[mid], sequence[end]

	slowsort(snake_case__ , snake_case__ , end - 1       )


if __name__ == "__main__":
							from doctest import testmod

							testmod()

