



"""simple docstring"""







import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


lowercase__		:    List[Any]				   =     5_0_0_0_0
lowercase__		:    Optional[Any]				   =     5_0_0_0

lowercase__   ,					lowercase__		:    int				   =     os.path.split(__file__)
lowercase__		:    Optional[Any]				   =     os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))

@get_duration
def     UpperCamelCase_   (   lowerCAmelCase__				:    List[Any]   ,       lowerCAmelCase__				:    int						):

  """simple docstring"""




  for i in range(_lowerCAmelCase						):
    lowerCAmelCase_       :    Optional[Any]								=			dataset[i]

@get_duration
def     UpperCamelCase_   (   lowerCAmelCase__				:    Union[str, Any]   ,       lowerCAmelCase__				:    List[str]   ,       lowerCAmelCase__				:    Dict						):

  """simple docstring"""




  for i in range(0   ,       len(_lowerCAmelCase						)   ,       _lowerCAmelCase						):
    lowerCAmelCase_       :    Optional[int]								=			dataset[i : i + batch_size]

@get_duration
def     UpperCamelCase_   (   lowerCAmelCase__				:    Optional[Any]   ,       lowerCAmelCase__				:    List[str]   ,       lowerCAmelCase__				:    Dict						):

  """simple docstring"""




  with dataset.formatted_as(type=_lowerCAmelCase						):
    for i in range(_lowerCAmelCase						):
      lowerCAmelCase_       :    Optional[Any]								=			dataset[i]

@get_duration
def     UpperCamelCase_   (   lowerCAmelCase__				:    int   ,       lowerCAmelCase__				:    int   ,       lowerCAmelCase__				:    str   ,       lowerCAmelCase__				:    str						):

  """simple docstring"""




  with dataset.formatted_as(type=_lowerCAmelCase						):
    for i in range(0   ,       _lowerCAmelCase   ,       _lowerCAmelCase						):
      lowerCAmelCase_       :    Tuple								=			dataset[i : i + batch_size]

def     UpperCamelCase_   (   ):

  """simple docstring"""




  lowerCAmelCase_       :    List[str]								=			{"""num examples""": SPEED_TEST_N_EXAMPLES}
  lowerCAmelCase_       :    Dict								=			[
      (read, {"""length""": SMALL_TEST}),
      (read, {"""length""": SPEED_TEST_N_EXAMPLES}),
      (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 10}),
      (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 100}),
      (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 1000}),
      (read_formatted, {"""type""": """numpy""", """length""": SMALL_TEST}),
      (read_formatted, {"""type""": """pandas""", """length""": SMALL_TEST}),
      (read_formatted, {"""type""": """torch""", """length""": SMALL_TEST}),
      (read_formatted, {"""type""": """tensorflow""", """length""": SMALL_TEST}),
      (read_formatted_batch, {"""type""": """numpy""", """length""": SMALL_TEST, """batch_size""": 10}),
      (read_formatted_batch, {"""type""": """numpy""", """length""": SMALL_TEST, """batch_size""": 1000}),
  ]

  lowerCAmelCase_       :    List[str]								=			[
      (read, {"""length""": SMALL_TEST}),
      (read, {"""length""": SPEED_TEST_N_EXAMPLES}),
      (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 10}),
      (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 100}),
      (read_batch, {"""length""": SPEED_TEST_N_EXAMPLES, """batch_size""": 1000}),
      (read_formatted, {"""type""": """numpy""", """length""": SMALL_TEST}),
      (read_formatted_batch, {"""type""": """numpy""", """length""": SMALL_TEST, """batch_size""": 10}),
      (read_formatted_batch, {"""type""": """numpy""", """length""": SMALL_TEST, """batch_size""": 1000}),
  ]
  with tempfile.TemporaryDirectory() as tmp_dir:
    print('generating dataset'						)
    lowerCAmelCase_       :    Tuple								=			datasets.Features(
        {'list': datasets.Sequence(datasets.Value('float32'						)						), 'numbers': datasets.Value('float32'						)}						)
    lowerCAmelCase_       :    Optional[int]								=			generate_example_dataset(
        os.path.join(_lowerCAmelCase   ,       'dataset.arrow'						)   ,       _lowerCAmelCase   ,       num_examples=_lowerCAmelCase   ,       seq_shapes={'list': (100,)}   ,       )
    print('first set of iterations'						)
    for func, kwargs in functions:
      print(func.__name__   ,       str(_lowerCAmelCase						)						)
      lowerCAmelCase_       :    Dict								=			func(_lowerCAmelCase   ,       **_lowerCAmelCase						)

    print('shuffling dataset'						)
    lowerCAmelCase_       :    Dict								=			dataset.shuffle()
    print('Second set of iterations (after shuffling'						)
    for func, kwargs in functions_shuffled:
      print('shuffled '   ,       func.__name__   ,       str(_lowerCAmelCase						)						)
      lowerCAmelCase_       :    List[str]								=			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_iterating()










"""simple docstring"""







from collections.abc import Iterable
from typing import Generic, TypeVar

lowercase__		:    Any				   =     TypeVar("""_T""")







class 				UpperCamelCase__       (     Generic[_T]  ):




      """simple docstring"""




      def __init__(				self    :				Any   ,      SCREAMING_SNAKE_CASE_    :				Iterable[_T] | None = None	):
        lowerCAmelCase_       :    list[_T]								=			list(iterable or []	)
        lowerCAmelCase_       :    list[_T]								=			[]



      def __len__(				self    :				List[str]	):
        return len(self._stacka	) + len(self._stacka	)



      def __repr__(				self    :				int	):
        return F"Queue({tuple(self._stacka[::-1] + self._stacka	)})"



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Tuple   ,      SCREAMING_SNAKE_CASE_    :				_T	):
        self._stacka.append(SCREAMING_SNAKE_CASE_	)





      def 					SCREAMING_SNAKE_CASE__			(				self    :				str	):
        lowerCAmelCase_       :    List[str]								=			self._stacka.pop
        lowerCAmelCase_       :    int								=			self._stacka.append

        if not self._stacka:
          while self._stacka:
            stacka_append(stacka_pop()	)

        if not self._stacka:
          raise IndexError('Queue is empty'	)
        return self._stacka.pop()


if __name__ == "__main__":
     from doctest import testmod

     testmod()





