



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 :				Union[str, Any]							=(30, 487)
UpperCAmelCase :				Tuple							=(36, 1024)
UpperCAmelCase :				str							=(100, 100)
UpperCAmelCase :				Dict							=100

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

UpperCAmelCase			,			UpperCAmelCase :				Tuple							=os.path.split(__file__)
UpperCAmelCase :				str							=os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase):
					with ArrowWriter(features=_lowerCAmelCase ,						path=os.path.join(_lowerCAmelCase ,						"beta.arrow")) as writer:
										for key, record in dummy_data:
															UpperCamelCase_			= my_features.encode_example(_lowerCAmelCase)
															writer.write(_lowerCAmelCase)
										UpperCamelCase_	,     UpperCamelCase_			= writer.finalize()



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= 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 ,						_lowerCAmelCase):
					UpperCamelCase_			= 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 ,						_lowerCAmelCase):
					UpperCamelCase_			= 10
					UpperCamelCase_			= datasets.Dataset.from_file(
					    filename=os.path.join(_lowerCAmelCase ,						"beta.arrow") ,						info=datasets.DatasetInfo(features=_lowerCAmelCase))
					for i in range(0 ,						len(_lowerCAmelCase) ,						_lowerCAmelCase):
										UpperCamelCase_			= dataset[i : i + batch_size]



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= 10
					UpperCamelCase_			= 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):
										UpperCamelCase_			= dataset[i : i + batch_size]



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= datasets.Dataset.from_file(
					    filename=os.path.join(_lowerCAmelCase ,						"beta.arrow") ,						info=datasets.DatasetInfo(features=_lowerCAmelCase))
					for col in feats:
										UpperCamelCase_			= dataset[col]



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= datasets.Dataset.from_file(
					    filename=os.path.join(_lowerCAmelCase ,						"beta.arrow") ,						info=datasets.DatasetInfo(features=_lowerCAmelCase))
					dataset.set_format("numpy")
					for col in feats:
										UpperCamelCase_			= dataset[col]



def  _lowerCAmelCase     ():
					UpperCamelCase_			= {}
					UpperCamelCase_			= (
					    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:
										UpperCamelCase_			= datasets.Features({"image": ArrayaD(_lowerCAmelCase ,						dtype="float32")})
										UpperCamelCase_			= generate_examples(features=_lowerCAmelCase ,						num_examples=_lowerCAmelCase)
										UpperCamelCase_			= write(_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase)
										for read_func in read_functions:
															UpperCamelCase_			= 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])}
										# )
										UpperCamelCase_			= datasets.Features({"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))})
										UpperCamelCase_			= generate_examples(
										    features=_lowerCAmelCase ,						num_examples=_lowerCAmelCase ,						seq_shapes={"image": SPEED_TEST_SHAPE})
										UpperCamelCase_			= write(_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase)
										for read_func in read_functions:
															UpperCamelCase_			= 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])}
										# )
										UpperCamelCase_			= datasets.Features({"image": datasets.Sequence(datasets.Value("float32"))})
										UpperCamelCase_			= generate_examples(
										    features=_lowerCAmelCase ,						num_examples=_lowerCAmelCase ,						seq_shapes={"image": [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]} ,						)
										UpperCamelCase_			= write(_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase)
										for read_func in read_functions:
															UpperCamelCase_			= 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   a_					(_lowerCAmelCase  :   int       )->				str:
    if not isinstance(_lowerCAmelCase			,	_lowerCAmelCase       ):
        snake_case:						Optional[Any]         =   (
            """operation can not be conducted on a object of type """
            F"{type(_lowerCAmelCase       ).__name__}"
        )
        raise TypeError(_lowerCAmelCase       )
    snake_case:						List[Any]         =   """"""
    for _ in range(0			,	32       ):
        bit_string += str(number % 2       )
        snake_case:						Any         =   number >> 1
    return bit_string

def   a_					(_lowerCAmelCase  :   int       )->				str:
    if number < 0:
        raise ValueError("""the value of input must be positive"""       )
    elif isinstance(_lowerCAmelCase			,	_lowerCAmelCase       ):
        raise TypeError("""Input value must be a 'int' type"""       )
    elif isinstance(_lowerCAmelCase			,	_lowerCAmelCase       ):
        raise TypeError("""'<' not supported between instances of 'str' and 'int'"""       )
    snake_case:						Optional[Any]         =   0
    # iterator over [1 to 32],since we are dealing with 32 bit integer
    for _ in range(1			,	33       ):
        # left shift the bits by unity
        snake_case:						Dict         =   result << 1
        # get the end bit
        snake_case:						Union[str, Any]         =   number % 2
        # right shift the bits by unity
        snake_case:						Union[str, Any]         =   number >> 1
        # add that bit to our ans
        snake_case:						Tuple         =   result | end_bit
    return get_reverse_bit_string(_lowerCAmelCase       )


if __name__ == "__main__":
    import doctest

    doctest.testmod()


