

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 						UpperCamelCase_(			snake_case__:  List[Any]  ,    snake_case__:  Dict  ,    snake_case__:  Dict   )       -> Optional[Any]:
 with ArrowWriter(features=snake_case__  ,    path=os.path.join(snake_case__  ,    'beta.arrow'   )   ) as writer:
  for key, record in dummy_data:
   UpperCAmelCase__							=				my_features.encode_example(snake_case__   )
   writer.write(snake_case__   )
  UpperCAmelCase__				,    UpperCAmelCase__							=				writer.finalize()
@get_duration
def 						UpperCamelCase_(			snake_case__:  List[Any]  ,    snake_case__:  str   )       -> Union[str, Any]:
 UpperCAmelCase__							=				datasets.Dataset.from_file(
     filename=os.path.join(snake_case__  ,    'beta.arrow'   )  ,    info=datasets.DatasetInfo(features=snake_case__   )   )
 for _ in dataset:
  pass
@get_duration
def 						UpperCamelCase_(			snake_case__:  Tuple  ,    snake_case__:  Union[str, Any]   )       -> Any:
 UpperCAmelCase__							=				datasets.Dataset.from_file(
     filename=os.path.join(snake_case__  ,    'beta.arrow'   )  ,    info=datasets.DatasetInfo(features=snake_case__   )   )
 dataset.set_format('numpy'   )
 for _ in dataset:
  pass
@get_duration
def 						UpperCamelCase_(			snake_case__:  List[Any]  ,    snake_case__:  List[Any]   )       -> Union[str, Any]:
 UpperCAmelCase__							=				10
 UpperCAmelCase__							=				datasets.Dataset.from_file(
     filename=os.path.join(snake_case__  ,    'beta.arrow'   )  ,    info=datasets.DatasetInfo(features=snake_case__   )   )
 for i in range(0  ,    len(snake_case__   )  ,    snake_case__   ):
  UpperCAmelCase__							=				dataset[i : i + batch_size]
@get_duration
def 						UpperCamelCase_(			snake_case__:  List[Any]  ,    snake_case__:  Dict   )       -> Any:
 UpperCAmelCase__							=				10
 UpperCAmelCase__							=				datasets.Dataset.from_file(
     filename=os.path.join(snake_case__  ,    'beta.arrow'   )  ,    info=datasets.DatasetInfo(features=snake_case__   )   )
 dataset.set_format('numpy'   )
 for i in range(0  ,    len(snake_case__   )  ,    snake_case__   ):
  UpperCAmelCase__							=				dataset[i : i + batch_size]
@get_duration
def 						UpperCamelCase_(			snake_case__:  Tuple  ,    snake_case__:  List[str]   )       -> Union[str, Any]:
 UpperCAmelCase__							=				datasets.Dataset.from_file(
     filename=os.path.join(snake_case__  ,    'beta.arrow'   )  ,    info=datasets.DatasetInfo(features=snake_case__   )   )
 for col in feats:
  UpperCAmelCase__							=				dataset[col]
@get_duration
def 						UpperCamelCase_(			snake_case__:  List[Any]  ,    snake_case__:  Tuple   )       -> Dict:
 UpperCAmelCase__							=				datasets.Dataset.from_file(
     filename=os.path.join(snake_case__  ,    'beta.arrow'   )  ,    info=datasets.DatasetInfo(features=snake_case__   )   )
 dataset.set_format('numpy'   )
 for col in feats:
  UpperCAmelCase__							=				dataset[col]
def 						UpperCamelCase_(			)       -> Dict:
 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(snake_case__  ,    dtype='float32'   )}   )
  UpperCAmelCase__							=				generate_examples(features=snake_case__  ,    num_examples=snake_case__   )
  UpperCAmelCase__							=				write(snake_case__  ,    snake_case__  ,    snake_case__   )
  for read_func in read_functions:
   UpperCAmelCase__							=				read_func(snake_case__  ,    snake_case__   )

 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=snake_case__  ,    num_examples=snake_case__  ,    seq_shapes={'image': SPEED_TEST_SHAPE}   )
  UpperCAmelCase__							=				write(snake_case__  ,    snake_case__  ,    snake_case__   )
  for read_func in read_functions:
   UpperCAmelCase__							=				read_func(snake_case__  ,    snake_case__   )

 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=snake_case__  ,    num_examples=snake_case__  ,    seq_shapes={'image': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}  ,    )
  UpperCAmelCase__							=				write(snake_case__  ,    snake_case__  ,    snake_case__   )
  for read_func in read_functions:
   UpperCAmelCase__							=				read_func(snake_case__  ,    snake_case__   )

 with open(snake_case__  ,    'wb'   ) as f:
  f.write(json.dumps(snake_case__   ).encode('utf-8'   )   )


if __name__ == "__main__":  # useful to run the profiler
 benchmark_array_xd()




def 							lowerCAmelCase(	__lowerCamelCase      ,				__lowerCamelCase						):
					sequence.append(__lowerCamelCase						)

					__a							=   0
					while sequence[index] != target:
										index += 1

					sequence.pop()

					if index == len(__lowerCamelCase						):
										return None

					return index


if __name__ == "__main__":
	lowerCamelCase_				:		List[str]       						=       input("""Enter numbers separated by comma:\n""").strip()
	lowerCamelCase_				:		str       						=       [int(item) for item in user_input.split(""",""")]

	lowerCamelCase_				:		Tuple       						=       input("""Enter a single number to be found in the list:\n""")
	lowerCamelCase_				:		Optional[int]       						=       int(target_input)
	lowerCamelCase_				:		List[Any]       						=       sentinel_linear_search(sequence, target)
	if result is not None:
		print(F'''{target} found at positions: {result}''')
	else:
		print("""Not found""")




