



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


UpperCAmelCase_		   =				(3_0, 4_8_7)
UpperCAmelCase_		   =				(3_6, 1_0_2_4)
UpperCAmelCase_		   =				(1_0_0, 1_0_0)
UpperCAmelCase_		   =				1_0_0

UpperCAmelCase_		   =				datasets.Features(
    {"""text""": ArrayaD(SHAPE_TEST_1, dtype="""float32"""), """image""": ArrayaD(SHAPE_TEST_2, dtype="""float32""")}
)

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

@get_duration
def   SCREAMING_SNAKE_CASE_       (  _snake_case  :Optional[Any]  ,      _snake_case  :Optional[int]  ,      _snake_case  :int							)     ->    Optional[Any]:
   with ArrowWriter(features=_snake_case  ,      path=os.path.join(_snake_case  ,      '''beta.arrow'''							)							) as writer:
      for key, record in dummy_data:
         _A						     =					my_features.encode_example(_snake_case							)
         writer.write(_snake_case							)
      _A     ,						_A						     =					writer.finalize()

@get_duration
def   SCREAMING_SNAKE_CASE_       (  _snake_case  :int  ,      _snake_case  :Optional[Any]							)     ->    Any:
   _A						     =					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  :Optional[int]  ,      _snake_case  :int							)     ->    Any:
   _A						     =					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  :Optional[int]  ,      _snake_case  :Union[str, Any]							)     ->    Optional[Any]:
   _A						     =					10
   _A						     =					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							):
      _A						     =					dataset[i : i + batch_size]

@get_duration
def   SCREAMING_SNAKE_CASE_       (  _snake_case  :Union[str, Any]  ,      _snake_case  :Dict							)     ->    int:
   _A						     =					10
   _A						     =					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							):
      _A						     =					dataset[i : i + batch_size]

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

@get_duration
def   SCREAMING_SNAKE_CASE_       (  _snake_case  :Dict  ,      _snake_case  :List[str]							)     ->    Tuple:
   _A						     =					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:
      _A						     =					dataset[col]

def   SCREAMING_SNAKE_CASE_       (  )     ->    Any:
   _A						     =					{}
   _A						     =					(
       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:
      _A						     =					datasets.Features({'''image''': ArrayaD(_snake_case  ,      dtype='''float32'''							)}							)
      _A						     =					generate_examples(features=_snake_case  ,      num_examples=_snake_case							)
      _A						     =					write(_snake_case  ,      _snake_case  ,      _snake_case							)
      for read_func in read_functions:
         _A						     =					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])}
      # )
      _A						     =					datasets.Features({'''image''': datasets.Sequence(datasets.Sequence(datasets.Value('''float32'''							)							)							)}							)
      _A						     =					generate_examples(
          features=_snake_case  ,      num_examples=_snake_case  ,      seq_shapes={'''image''': SPEED_TEST_SHAPE}							)
      _A						     =					write(_snake_case  ,      _snake_case  ,      _snake_case							)
      for read_func in read_functions:
         _A						     =					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])}
      # )
      _A						     =					datasets.Features({'''image''': datasets.Sequence(datasets.Value('''float32'''							)							)}							)
      _A						     =					generate_examples(
          features=_snake_case  ,      num_examples=_snake_case  ,      seq_shapes={'''image''': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}  ,      )
      _A						     =					write(_snake_case  ,      _snake_case  ,      _snake_case							)
      for read_func in read_functions:
         _A						     =					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()








def   SCREAMING_SNAKE_CASE_       (  _snake_case  :list							)     ->    list:
   if len(_snake_case							) <= 1:
      return data
   else:
      return [
          *quick_sort([e for e in data[1:] if e <= data[0]]							),
          data[0],
          *quick_sort([e for e in data[1:] if e > data[0]]							),
      ]


if __name__ == "__main__":
   import doctest

   doctest.testmod()



