




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, 4_87)
_lowerCamelCase			 =						(36, 10_24)
_lowerCamelCase			 =						(1_00, 1_00)
_lowerCamelCase			 =						1_00

_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 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						Dict       ,     __UpperCamelCase			:						Optional[int]       ,     __UpperCamelCase			:						Optional[int]      )  ->							Dict:
    with ArrowWriter(features=__UpperCamelCase       ,     path=os.path.join(__UpperCamelCase       ,     '''beta.arrow'''      )      ) as writer:
        for key, record in dummy_data:
            UpperCAmelCase_							 =     my_features.encode_example(__UpperCamelCase      )
            writer.write(__UpperCamelCase      )
        UpperCAmelCase_ ,							UpperCAmelCase_							 =     writer.finalize()




@get_duration
def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						List[str]       ,     __UpperCamelCase			:						List[str]      )  ->							Dict:
    UpperCAmelCase_							 =     datasets.Dataset.from_file(
        filename=os.path.join(__UpperCamelCase       ,     '''beta.arrow'''      )       ,     info=datasets.DatasetInfo(features=__UpperCamelCase      )      )
    for _ in dataset:
        pass




@get_duration
def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						Optional[Any]       ,     __UpperCamelCase			:						Any      )  ->							Any:
    UpperCAmelCase_							 =     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 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						str       ,     __UpperCamelCase			:						str      )  ->							Any:
    UpperCAmelCase_							 =     10
    UpperCAmelCase_							 =     datasets.Dataset.from_file(
        filename=os.path.join(__UpperCamelCase       ,     '''beta.arrow'''      )       ,     info=datasets.DatasetInfo(features=__UpperCamelCase      )      )
    for i in range(0       ,     len(__UpperCamelCase      )       ,     __UpperCamelCase      ):
        UpperCAmelCase_							 =     dataset[i : i + batch_size]




@get_duration
def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						Union[str, Any]       ,     __UpperCamelCase			:						Any      )  ->							Union[str, Any]:
    UpperCAmelCase_							 =     10
    UpperCAmelCase_							 =     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      ):
        UpperCAmelCase_							 =     dataset[i : i + batch_size]




@get_duration
def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						Optional[int]       ,     __UpperCamelCase			:						int      )  ->							Tuple:
    UpperCAmelCase_							 =     datasets.Dataset.from_file(
        filename=os.path.join(__UpperCamelCase       ,     '''beta.arrow'''      )       ,     info=datasets.DatasetInfo(features=__UpperCamelCase      )      )
    for col in feats:
        UpperCAmelCase_							 =     dataset[col]




@get_duration
def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						Optional[Any]       ,     __UpperCamelCase			:						List[Any]      )  ->							Dict:
    UpperCAmelCase_							 =     datasets.Dataset.from_file(
        filename=os.path.join(__UpperCamelCase       ,     '''beta.arrow'''      )       ,     info=datasets.DatasetInfo(features=__UpperCamelCase      )      )
    dataset.set_format('''numpy'''      )
    for col in feats:
        UpperCAmelCase_							 =     dataset[col]




def 					SCREAMING_SNAKE_CASE	(       )  ->							str:
    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(__UpperCamelCase       ,     dtype='''float32'''      )}      )
        UpperCAmelCase_							 =     generate_examples(features=__UpperCamelCase       ,     num_examples=__UpperCamelCase      )
        UpperCAmelCase_							 =     write(__UpperCamelCase       ,     __UpperCamelCase       ,     __UpperCamelCase      )
        for read_func in read_functions:
            UpperCAmelCase_							 =     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])}
        # )
        UpperCAmelCase_							 =     datasets.Features({'''image''': datasets.Sequence(datasets.Sequence(datasets.Value('''float32'''      )      )      )}      )
        UpperCAmelCase_							 =     generate_examples(
            features=__UpperCamelCase       ,     num_examples=__UpperCamelCase       ,     seq_shapes={'''image''': SPEED_TEST_SHAPE}      )
        UpperCAmelCase_							 =     write(__UpperCamelCase       ,     __UpperCamelCase       ,     __UpperCamelCase      )
        for read_func in read_functions:
            UpperCAmelCase_							 =     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])}
        # )
        UpperCAmelCase_							 =     datasets.Features({'''image''': datasets.Sequence(datasets.Value('''float32'''      )      )}      )
        UpperCAmelCase_							 =     generate_examples(
            features=__UpperCamelCase       ,     num_examples=__UpperCamelCase       ,     seq_shapes={'''image''': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}       ,     )
        UpperCAmelCase_							 =     write(__UpperCamelCase       ,     __UpperCamelCase       ,     __UpperCamelCase      )
        for read_func in read_functions:
            UpperCAmelCase_							 =     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()











def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						str      )  ->							int:
    UpperCAmelCase_							 =     5381
    for x in s:
        UpperCAmelCase_							 =     ((hash_value << 5) + hash_value) + ord(__UpperCamelCase      )
    return hash_value & 0xffff_ffff





