




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

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 							_A   (						lowerCAmelCase_     :					Dict   ,				lowerCAmelCase_     :					Optional[int]   ,				lowerCAmelCase_     :					Optional[int]			):
     """simple docstring"""

     with ArrowWriter(features=__UpperCamelCase   ,				path=os.path.join(__UpperCamelCase   ,				"beta.arrow"			)			) as writer:
          for key, record in dummy_data:
               lowerCAmelCase__		= my_features.encode_example(__UpperCamelCase			)
               writer.write(__UpperCamelCase			)
          lowerCAmelCase__	,		lowerCAmelCase__		= writer.finalize()



@get_duration
def 							_A   (						lowerCAmelCase_     :					List[str]   ,				lowerCAmelCase_     :					List[str]			):
     """simple docstring"""

     lowerCAmelCase__		= datasets.Dataset.from_file(
         filename=os.path.join(__UpperCamelCase   ,				"beta.arrow"			)   ,				info=datasets.DatasetInfo(features=__UpperCamelCase			)			)
     for _ in dataset:
          pass



@get_duration
def 							_A   (						lowerCAmelCase_     :					Optional[Any]   ,				lowerCAmelCase_     :					Any			):
     """simple docstring"""

     lowerCAmelCase__		= 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   (						lowerCAmelCase_     :					str   ,				lowerCAmelCase_     :					str			):
     """simple docstring"""

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



@get_duration
def 							_A   (						lowerCAmelCase_     :					Union[str, Any]   ,				lowerCAmelCase_     :					Any			):
     """simple docstring"""

     lowerCAmelCase__		= 10
     lowerCAmelCase__		= 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			):
          lowerCAmelCase__		= dataset[i : i + batch_size]



@get_duration
def 							_A   (						lowerCAmelCase_     :					Optional[int]   ,				lowerCAmelCase_     :					int			):
     """simple docstring"""

     lowerCAmelCase__		= datasets.Dataset.from_file(
         filename=os.path.join(__UpperCamelCase   ,				"beta.arrow"			)   ,				info=datasets.DatasetInfo(features=__UpperCamelCase			)			)
     for col in feats:
          lowerCAmelCase__		= dataset[col]



@get_duration
def 							_A   (						lowerCAmelCase_     :					Optional[Any]   ,				lowerCAmelCase_     :					List[Any]			):
     """simple docstring"""

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



def 							_A   (						):
     """simple docstring"""

     lowerCAmelCase__		= {}
     lowerCAmelCase__		= (
         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:
          lowerCAmelCase__		= datasets.Features({"image": ArrayaD(__UpperCamelCase   ,				dtype="float32"			)}			)
          lowerCAmelCase__		= generate_examples(features=__UpperCamelCase   ,				num_examples=__UpperCamelCase			)
          lowerCAmelCase__		= write(__UpperCamelCase   ,				__UpperCamelCase   ,				__UpperCamelCase			)
          for read_func in read_functions:
               lowerCAmelCase__		= 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])}
          # )
          lowerCAmelCase__		= datasets.Features({"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32"			)			)			)}			)
          lowerCAmelCase__		= generate_examples(
              features=__UpperCamelCase   ,				num_examples=__UpperCamelCase   ,				seq_shapes={"image": SPEED_TEST_SHAPE}			)
          lowerCAmelCase__		= write(__UpperCamelCase   ,				__UpperCamelCase   ,				__UpperCamelCase			)
          for read_func in read_functions:
               lowerCAmelCase__		= 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])}
          # )
          lowerCAmelCase__		= datasets.Features({"image": datasets.Sequence(datasets.Value("float32"			)			)}			)
          lowerCAmelCase__		= generate_examples(
              features=__UpperCamelCase   ,				num_examples=__UpperCamelCase   ,				seq_shapes={"image": [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}   ,				)
          lowerCAmelCase__		= write(__UpperCamelCase   ,				__UpperCamelCase   ,				__UpperCamelCase			)
          for read_func in read_functions:
               lowerCAmelCase__		= 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			:						float       ,     __UpperCamelCase			:						float      )  ->							float:
    return a + b


if __name__ == "__main__":
 _lowerCamelCase			 =						5
 _lowerCamelCase			 =						6
 print(F"The sum of {a} + {b} is {add(a, b)}")





