code: 
  
  
  
  
  """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
  
  
  SCREAMING_SNAKE_CASE       = (30, 487)
  SCREAMING_SNAKE_CASE       = (36, 1024)
  SCREAMING_SNAKE_CASE       = (100, 100)
  SCREAMING_SNAKE_CASE       = 100
  
  SCREAMING_SNAKE_CASE       = datasets.Features(
      {"text": ArrayaD(SHAPE_TEST_1, dtype="float32"), "image": ArrayaD(SHAPE_TEST_2, dtype="float32")}
  )
  
  SCREAMING_SNAKE_CASE,      SCREAMING_SNAKE_CASE       = os.path.split(__file__)
  SCREAMING_SNAKE_CASE       = os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_    ,				lowercase_		)		->	Union[str, Any]:
   with ArrowWriter(features=lowercase_    ,				path=os.path.join(lowercase_    ,				"beta.arrow"		)		) as writer:
    for key, record in dummy_data:
     A__ =       my_features.encode_example(lowercase_		)
     writer.write(lowercase_		)
    A__,   A__ =       writer.finalize()
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_		)		->	Optional[Any]:
   A__ =       datasets.Dataset.from_file(
       filename=os.path.join(lowercase_    ,				"beta.arrow"		)    ,				info=datasets.DatasetInfo(features=lowercase_		)		)
   for _ in dataset:
    pass
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_		)		->	Union[str, Any]:
   A__ =       datasets.Dataset.from_file(
       filename=os.path.join(lowercase_    ,				"beta.arrow"		)    ,				info=datasets.DatasetInfo(features=lowercase_		)		)
   dataset.set_format("numpy"		)
   for _ in dataset:
    pass
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_		)		->	List[str]:
   A__ =       10
   A__ =       datasets.Dataset.from_file(
       filename=os.path.join(lowercase_    ,				"beta.arrow"		)    ,				info=datasets.DatasetInfo(features=lowercase_		)		)
   for i in range(0    ,				len(lowercase_		)    ,				lowercase_		):
    A__ =       dataset[i : i + batch_size]
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_		)		->	Dict:
   A__ =       10
   A__ =       datasets.Dataset.from_file(
       filename=os.path.join(lowercase_    ,				"beta.arrow"		)    ,				info=datasets.DatasetInfo(features=lowercase_		)		)
   dataset.set_format("numpy"		)
   for i in range(0    ,				len(lowercase_		)    ,				lowercase_		):
    A__ =       dataset[i : i + batch_size]
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_		)		->	str:
   A__ =       datasets.Dataset.from_file(
       filename=os.path.join(lowercase_    ,				"beta.arrow"		)    ,				info=datasets.DatasetInfo(features=lowercase_		)		)
   for col in feats:
    A__ =       dataset[col]
  
  
  
  
  
  
  
  @get_duration
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_    ,				lowercase_		)		->	List[str]:
   A__ =       datasets.Dataset.from_file(
       filename=os.path.join(lowercase_    ,				"beta.arrow"		)    ,				info=datasets.DatasetInfo(features=lowercase_		)		)
   dataset.set_format("numpy"		)
   for col in feats:
    A__ =       dataset[col]
  
  
  
  
  
  
  
  def 						_SCREAMING_SNAKE_CASE     (							)		->	str:
   A__ =       {}
   A__ =       (
       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__ =       datasets.Features({"image": ArrayaD(lowercase_    ,				dtype="float32"		)}		)
    A__ =       generate_examples(features=lowercase_    ,				num_examples=lowercase_		)
    A__ =       write(lowercase_    ,				lowercase_    ,				lowercase_		)
    for read_func in read_functions:
     A__ =       read_func(lowercase_    ,				lowercase_		)
  
   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__ =       datasets.Features({"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32"		)		)		)}		)
    A__ =       generate_examples(
        features=lowercase_    ,				num_examples=lowercase_    ,				seq_shapes={"image": SPEED_TEST_SHAPE}		)
    A__ =       write(lowercase_    ,				lowercase_    ,				lowercase_		)
    for read_func in read_functions:
     A__ =       read_func(lowercase_    ,				lowercase_		)
  
   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__ =       datasets.Features({"image": datasets.Sequence(datasets.Value("float32"		)		)}		)
    A__ =       generate_examples(
        features=lowercase_    ,				num_examples=lowercase_    ,				seq_shapes={"image": [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}    ,				)
    A__ =       write(lowercase_    ,				lowercase_    ,				lowercase_		)
    for read_func in read_functions:
     A__ =       read_func(lowercase_    ,				lowercase_		)
  
   with open(lowercase_    ,				"wb"		) as f:
    f.write(json.dumps(lowercase_		).encode("utf-8"		)		)
  
  
  if __name__ == "__main__":  # useful to run the profiler
         benchmark_array_xd()
  
  
  
  
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  
  
  from transformers import PretrainedConfig
  
  
  
  
  class 			UpperCAmelCase_						(		A_							):
      lowercase__		      =   '''custom'''
  
  
  
  
      def __init__(					self		: Any			,				snake_case_		: List[Any]=1			,				**snake_case_		: Any   )   ->							str:
  
  
  
  
       '''simple docstring'''
  
       A__ =       attribute
       super().__init__(**snake_case_   )
  
  
  
  
  
  
  class 			UpperCAmelCase_						(		A_							):
      lowercase__		      =   '''custom'''
  
  
  
  
      def __init__(					self		: Any			,				snake_case_		: Tuple=1			,				**snake_case_		: Dict   )   ->							Any:
  
  
  
  
       '''simple docstring'''
  
       A__ =       attribute
  
  
  
  
  
  