






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__		:       str   							=							(30, 4_87)
SCREAMING_SNAKE_CASE__		:       Any   							=							(36, 10_24)
SCREAMING_SNAKE_CASE__		:       List[Any]   							=							(1_00, 1_00)
SCREAMING_SNAKE_CASE__		:       Any   							=							1_00

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

SCREAMING_SNAKE_CASE__		:       Tuple   							=							os.path.split(__file__)
SCREAMING_SNAKE_CASE__		:       List[Any]   							=							os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))





@get_duration
def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)   -> Any:

					'''simple docstring'''
					with ArrowWriter(features=__lowerCamelCase   ,       path=os.path.join(__lowerCamelCase   ,       """beta.arrow"""					)					) as writer:
										for key, record in dummy_data:
															UpperCAmelCase__			:     int										= my_features.encode_example(__lowerCamelCase					)
															writer.write(__lowerCamelCase					)
										UpperCAmelCase__			:     List[str]										= writer.finalize()





@get_duration
def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> Optional[int]:

					'''simple docstring'''
					UpperCAmelCase__			:     Optional[Any]										= 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					)   -> Dict:

					'''simple docstring'''
					UpperCAmelCase__			:     List[str]										= 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					)   -> str:

					'''simple docstring'''
					UpperCAmelCase__			:     Optional[Any]										= 10
					UpperCAmelCase__			:     str										= 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__			:     str										= dataset[i : i + batch_size]





@get_duration
def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> int:

					'''simple docstring'''
					UpperCAmelCase__			:     List[Any]										= 10
					UpperCAmelCase__			:     Tuple										= 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__			:     str										= dataset[i : i + batch_size]





@get_duration
def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> List[Any]:

					'''simple docstring'''
					UpperCAmelCase__			:     Union[str, Any]										= datasets.Dataset.from_file(
					    filename=os.path.join(__lowerCamelCase   ,       """beta.arrow"""					)   ,       info=datasets.DatasetInfo(features=__lowerCamelCase					)					)
					for col in feats:
										UpperCAmelCase__			:     Union[str, Any]										= dataset[col]





@get_duration
def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> List[Any]:

					'''simple docstring'''
					UpperCAmelCase__			:     Any										= 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__			:     Union[str, Any]										= dataset[col]





def    _lowerCamelCase	(	)   -> str:

					'''simple docstring'''
					UpperCAmelCase__			:     Any										= {}
					UpperCAmelCase__			:     str										= (
					    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__			:     Optional[Any]										= datasets.Features({"""image""": ArrayaD(__lowerCamelCase   ,       dtype="""float32"""					)}					)
										UpperCAmelCase__			:     List[str]										= generate_examples(features=__lowerCamelCase   ,       num_examples=__lowerCamelCase					)
										UpperCAmelCase__			:     Optional[Any]										= write(__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)
										for read_func in read_functions:
															UpperCAmelCase__			:     Union[str, Any]										= 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__			:     List[Any]										= datasets.Features({"""image""": datasets.Sequence(datasets.Sequence(datasets.Value("""float32"""					)					)					)}					)
										UpperCAmelCase__			:     List[Any]										= generate_examples(
										    features=__lowerCamelCase   ,       num_examples=__lowerCamelCase   ,       seq_shapes={"""image""": SPEED_TEST_SHAPE}					)
										UpperCAmelCase__			:     Dict										= write(__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)
										for read_func in read_functions:
															UpperCAmelCase__			:     Union[str, Any]										= 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__			:     Tuple										= datasets.Features({"""image""": datasets.Sequence(datasets.Value("""float32"""					)					)}					)
										UpperCAmelCase__			:     Any										= generate_examples(
										    features=__lowerCamelCase   ,       num_examples=__lowerCamelCase   ,       seq_shapes={"""image""": [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}   ,       )
										UpperCAmelCase__			:     Optional[int]										= write(__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)
										for read_func in read_functions:
															UpperCAmelCase__			:     str										= 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()














from .stack import Stack





def    _lowerCamelCase	(	__lowerCamelCase					)   -> bool:

     '''simple docstring'''
     UpperCAmelCase__			:     Stack[str]										= Stack()
     UpperCAmelCase__			:     str										= {"""(""": """)""", """[""": """]""", """{""": """}"""}
     for bracket in parentheses:
          if bracket in bracket_pairs:
               stack.push(__lowerCamelCase					)
          elif bracket in (")", "]", "}"):
               if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
                    return False
     return stack.is_empty()


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

      testmod()

      SCREAMING_SNAKE_CASE__		:       Any   							=							["""((()))""", """((())""", """(()))"""]
      print("""Balanced parentheses demonstration:\n""")
      for example in examples:
            SCREAMING_SNAKE_CASE__		:       List[str]   							=							"""""" if balanced_parentheses(example) else """not """
            print(f'''{example} is {not_str}balanced''')






