



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


_lowerCamelCase         =	(30, 487)
_lowerCamelCase         =	(36, 1024)
_lowerCamelCase         =	(100, 100)
_lowerCamelCase         =	100

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

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






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  List[str]		,						__lowerCamelCase :  str		,						__lowerCamelCase :  List[Any]  ):



 """simple docstring"""





 with ArrowWriter(features=__lowerCamelCase		,						path=os.path.join(__lowerCamelCase		,						"beta.arrow"  )  ) as writer:
  for key, record in dummy_data:
   __SCREAMING_SNAKE_CASE							:     List[str]							=						my_features.encode_example(__lowerCamelCase  )
   writer.write(__lowerCamelCase  )
  __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE							:     int							=						writer.finalize()






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  int		,						__lowerCamelCase :  Optional[int]  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     List[Any]							=						datasets.Dataset.from_file(
     filename=os.path.join(__lowerCamelCase		,						"beta.arrow"  )		,						info=datasets.DatasetInfo(features=__lowerCamelCase  )  )
 for _ in dataset:
  pass






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  List[Any]		,						__lowerCamelCase :  Any  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     Tuple							=						datasets.Dataset.from_file(
     filename=os.path.join(__lowerCamelCase		,						"beta.arrow"  )		,						info=datasets.DatasetInfo(features=__lowerCamelCase  )  )
 dataset.set_format("numpy"  )
 for _ in dataset:
  pass






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  Optional[int]		,						__lowerCamelCase :  Optional[Any]  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     List[Any]							=						10
 __SCREAMING_SNAKE_CASE							:     Tuple							=						datasets.Dataset.from_file(
     filename=os.path.join(__lowerCamelCase		,						"beta.arrow"  )		,						info=datasets.DatasetInfo(features=__lowerCamelCase  )  )
 for i in range(0		,						len(__lowerCamelCase  )		,						__lowerCamelCase  ):
  __SCREAMING_SNAKE_CASE							:     Tuple							=						dataset[i : i + batch_size]






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  List[Any]		,						__lowerCamelCase :  Any  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     List[Any]							=						10
 __SCREAMING_SNAKE_CASE							:     Any							=						datasets.Dataset.from_file(
     filename=os.path.join(__lowerCamelCase		,						"beta.arrow"  )		,						info=datasets.DatasetInfo(features=__lowerCamelCase  )  )
 dataset.set_format("numpy"  )
 for i in range(0		,						len(__lowerCamelCase  )		,						__lowerCamelCase  ):
  __SCREAMING_SNAKE_CASE							:     List[Any]							=						dataset[i : i + batch_size]






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  Any		,						__lowerCamelCase :  str  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     List[str]							=						datasets.Dataset.from_file(
     filename=os.path.join(__lowerCamelCase		,						"beta.arrow"  )		,						info=datasets.DatasetInfo(features=__lowerCamelCase  )  )
 for col in feats:
  __SCREAMING_SNAKE_CASE							:     Dict							=						dataset[col]






@get_duration
def 						_lowerCAmelCase    (					__lowerCamelCase :  Dict		,						__lowerCamelCase :  Dict  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     List[Any]							=						datasets.Dataset.from_file(
     filename=os.path.join(__lowerCamelCase		,						"beta.arrow"  )		,						info=datasets.DatasetInfo(features=__lowerCamelCase  )  )
 dataset.set_format("numpy"  )
 for col in feats:
  __SCREAMING_SNAKE_CASE							:     List[Any]							=						dataset[col]






def 						_lowerCAmelCase    (					):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     List[str]							=						{}
 __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						(
     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:
  __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						datasets.Features({"image": ArrayaD(__lowerCamelCase		,						dtype="float32"  )}  )
  __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						generate_examples(features=__lowerCamelCase		,						num_examples=__lowerCamelCase  )
  __SCREAMING_SNAKE_CASE							:     Tuple							=						write(__lowerCamelCase		,						__lowerCamelCase		,						__lowerCamelCase  )
  for read_func in read_functions:
   __SCREAMING_SNAKE_CASE							:     Tuple							=						read_func(__lowerCamelCase		,						__lowerCamelCase  )

 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])}
  # )
  __SCREAMING_SNAKE_CASE							:     Dict							=						datasets.Features({"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32"  )  )  )}  )
  __SCREAMING_SNAKE_CASE							:     str							=						generate_examples(
      features=__lowerCamelCase		,						num_examples=__lowerCamelCase		,						seq_shapes={"image": SPEED_TEST_SHAPE}  )
  __SCREAMING_SNAKE_CASE							:     List[Any]							=						write(__lowerCamelCase		,						__lowerCamelCase		,						__lowerCamelCase  )
  for read_func in read_functions:
   __SCREAMING_SNAKE_CASE							:     int							=						read_func(__lowerCamelCase		,						__lowerCamelCase  )

 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])}
  # )
  __SCREAMING_SNAKE_CASE							:     Tuple							=						datasets.Features({"image": datasets.Sequence(datasets.Value("float32"  )  )}  )
  __SCREAMING_SNAKE_CASE							:     int							=						generate_examples(
      features=__lowerCamelCase		,						num_examples=__lowerCamelCase		,						seq_shapes={"image": [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}		,						)
  __SCREAMING_SNAKE_CASE							:     Tuple							=						write(__lowerCamelCase		,						__lowerCamelCase		,						__lowerCamelCase  )
  for read_func in read_functions:
   __SCREAMING_SNAKE_CASE							:     int							=						read_func(__lowerCamelCase		,						__lowerCamelCase  )

 with open(__lowerCamelCase		,						"wb"  ) as f:
  f.write(json.dumps(__lowerCamelCase  ).encode("utf-8"  )  )


if __name__ == "__main__":  # useful to run the profiler
      benchmark_array_xd()











def 						_lowerCAmelCase    (					__lowerCamelCase :  list  ):



 """simple docstring"""





 if len(__lowerCamelCase  ) <= 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()






