






"""simple docstring"""


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 :    str      =			(30, 4_87)
_UpperCamelCase :    List[str]      =			(36, 10_24)
_UpperCamelCase :    Optional[Any]      =			(1_00, 1_00)
_UpperCamelCase :    Any      =			1_00

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

_UpperCamelCase    ,       _UpperCamelCase :    Union[str, Any]      =			os.path.split(__file__)
_UpperCamelCase :    List[Any]      =			os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))




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




@get_duration
def 					a			(  UpperCamelCase_				:					str  ,						UpperCamelCase_				:					Optional[int]		)	->		str:
 __A						:							Tuple      =						datasets.Dataset.from_file(
     filename=os.path.join(UpperCamelCase_  ,						'beta.arrow'		)  ,						info=datasets.DatasetInfo(features=UpperCamelCase_		)		)
 for _ in dataset:
  pass




@get_duration
def 					a			(  UpperCamelCase_				:					Any  ,						UpperCamelCase_				:					Optional[Any]		)	->		str:
 __A						:							Tuple      =						datasets.Dataset.from_file(
     filename=os.path.join(UpperCamelCase_  ,						'beta.arrow'		)  ,						info=datasets.DatasetInfo(features=UpperCamelCase_		)		)
 dataset.set_format('numpy'		)
 for _ in dataset:
  pass




@get_duration
def 					a			(  UpperCamelCase_				:					Dict  ,						UpperCamelCase_				:					Optional[Any]		)	->		int:
 __A						:							Union[str, Any]      =						1_0
 __A						:							Optional[int]      =						datasets.Dataset.from_file(
     filename=os.path.join(UpperCamelCase_  ,						'beta.arrow'		)  ,						info=datasets.DatasetInfo(features=UpperCamelCase_		)		)
 for i in range(0  ,						len(UpperCamelCase_		)  ,						UpperCamelCase_		):
  __A						:							Optional[int]      =						dataset[i : i + batch_size]




@get_duration
def 					a			(  UpperCamelCase_				:					Dict  ,						UpperCamelCase_				:					Any		)	->		Dict:
 __A						:							Dict      =						1_0
 __A						:							List[Any]      =						datasets.Dataset.from_file(
     filename=os.path.join(UpperCamelCase_  ,						'beta.arrow'		)  ,						info=datasets.DatasetInfo(features=UpperCamelCase_		)		)
 dataset.set_format('numpy'		)
 for i in range(0  ,						len(UpperCamelCase_		)  ,						UpperCamelCase_		):
  __A						:							List[str]      =						dataset[i : i + batch_size]




@get_duration
def 					a			(  UpperCamelCase_				:					Tuple  ,						UpperCamelCase_				:					int		)	->		str:
 __A						:							List[str]      =						datasets.Dataset.from_file(
     filename=os.path.join(UpperCamelCase_  ,						'beta.arrow'		)  ,						info=datasets.DatasetInfo(features=UpperCamelCase_		)		)
 for col in feats:
  __A						:							List[str]      =						dataset[col]




@get_duration
def 					a			(  UpperCamelCase_				:					str  ,						UpperCamelCase_				:					Union[str, Any]		)	->		Dict:
 __A						:							Tuple      =						datasets.Dataset.from_file(
     filename=os.path.join(UpperCamelCase_  ,						'beta.arrow'		)  ,						info=datasets.DatasetInfo(features=UpperCamelCase_		)		)
 dataset.set_format('numpy'		)
 for col in feats:
  __A						:							List[Any]      =						dataset[col]




def 					a			(  )	->		Dict:
 __A						:							List[Any]      =						{}
 __A						:							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:
  __A						:							str      =						datasets.Features({'image': ArrayaD(UpperCamelCase_  ,						dtype='float32'		)}		)
  __A						:							List[Any]      =						generate_examples(features=UpperCamelCase_  ,						num_examples=UpperCamelCase_		)
  __A						:							Optional[Any]      =						write(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)
  for read_func in read_functions:
   __A						:							str      =						read_func(UpperCamelCase_  ,						UpperCamelCase_		)

 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						:							Dict      =						datasets.Features({'image': datasets.Sequence(datasets.Sequence(datasets.Value('float32'		)		)		)}		)
  __A						:							Tuple      =						generate_examples(
      features=UpperCamelCase_  ,						num_examples=UpperCamelCase_  ,						seq_shapes={'image': SPEED_TEST_SHAPE}		)
  __A						:							Any      =						write(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)
  for read_func in read_functions:
   __A						:							int      =						read_func(UpperCamelCase_  ,						UpperCamelCase_		)

 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						:							str      =						datasets.Features({'image': datasets.Sequence(datasets.Value('float32'		)		)}		)
  __A						:							Union[str, Any]      =						generate_examples(
      features=UpperCamelCase_  ,						num_examples=UpperCamelCase_  ,						seq_shapes={'image': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}  ,						)
  __A						:							Tuple      =						write(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)
  for read_func in read_functions:
   __A						:							str      =						read_func(UpperCamelCase_  ,						UpperCamelCase_		)

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


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













"""simple docstring"""


def 					a			(  UpperCamelCase_				:					float		)	->		int:
 return int(UpperCamelCase_		) if x - int(UpperCamelCase_		) <= 0 else int(UpperCamelCase_		) + 1


if __name__ == "__main__":
   import doctest

   doctest.testmod()





