





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, 1_024)
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_       (							_lowercase ,		_lowercase ,		_lowercase     ):
						with ArrowWriter(features=_lowercase ,		path=os.path.join(_lowercase ,		'''beta.arrow'''     )     ) as writer:
												for key, record in dummy_data:
																		_UpperCamelCase    :      Tuple						     =					my_features.encode_example(_lowercase     )
																		writer.write(_lowercase     )
												_UpperCamelCase    :      List[str]						     =					writer.finalize()





@get_duration
def  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      Union[str, Any]						     =					datasets.Dataset.from_file(
						    filename=os.path.join(_lowercase ,		'''beta.arrow'''     ) ,		info=datasets.DatasetInfo(features=_lowercase     )     )
						for _ in dataset:
												pass





@get_duration
def  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      List[Any]						     =					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  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      Optional[int]						     =					10
						_UpperCamelCase    :      List[str]						     =					datasets.Dataset.from_file(
						    filename=os.path.join(_lowercase ,		'''beta.arrow'''     ) ,		info=datasets.DatasetInfo(features=_lowercase     )     )
						for i in range(0 ,		len(_lowercase     ) ,		_lowercase     ):
												_UpperCamelCase    :      Union[str, Any]						     =					dataset[i : i + batch_size]





@get_duration
def  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      List[str]						     =					10
						_UpperCamelCase    :      Tuple						     =					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     ):
												_UpperCamelCase    :      List[str]						     =					dataset[i : i + batch_size]





@get_duration
def  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      Dict						     =					datasets.Dataset.from_file(
						    filename=os.path.join(_lowercase ,		'''beta.arrow'''     ) ,		info=datasets.DatasetInfo(features=_lowercase     )     )
						for col in feats:
												_UpperCamelCase    :      List[str]						     =					dataset[col]





@get_duration
def  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      Optional[Any]						     =					datasets.Dataset.from_file(
						    filename=os.path.join(_lowercase ,		'''beta.arrow'''     ) ,		info=datasets.DatasetInfo(features=_lowercase     )     )
						dataset.set_format('''numpy'''     )
						for col in feats:
												_UpperCamelCase    :      Optional[int]						     =					dataset[col]





def  a_       (							):
						_UpperCamelCase    :      Any						     =					{}
						_UpperCamelCase    :      List[Any]						     =					(
						    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    :      int						     =					datasets.Features({'''image''': ArrayaD(_lowercase ,		dtype='''float32'''     )}     )
												_UpperCamelCase    :      Any						     =					generate_examples(features=_lowercase ,		num_examples=_lowercase     )
												_UpperCamelCase    :      Union[str, Any]						     =					write(_lowercase ,		_lowercase ,		_lowercase     )
												for read_func in read_functions:
																		_UpperCamelCase    :      Dict						     =					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])}
												# )
												_UpperCamelCase    :      Dict						     =					datasets.Features({'''image''': datasets.Sequence(datasets.Sequence(datasets.Value('''float32'''     )     )     )}     )
												_UpperCamelCase    :      Optional[int]						     =					generate_examples(
												    features=_lowercase ,		num_examples=_lowercase ,		seq_shapes={'''image''': SPEED_TEST_SHAPE}     )
												_UpperCamelCase    :      Optional[int]						     =					write(_lowercase ,		_lowercase ,		_lowercase     )
												for read_func in read_functions:
																		_UpperCamelCase    :      Any						     =					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])}
												# )
												_UpperCamelCase    :      List[str]						     =					datasets.Features({'''image''': datasets.Sequence(datasets.Value('''float32'''     )     )}     )
												_UpperCamelCase    :      Tuple						     =					generate_examples(
												    features=_lowercase ,		num_examples=_lowercase ,		seq_shapes={'''image''': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]} ,		)
												_UpperCamelCase    :      List[Any]						     =					write(_lowercase ,		_lowercase ,		_lowercase     )
												for read_func in read_functions:
																		_UpperCamelCase    :      Any						     =					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()










"""simple docstring"""




def  a_       (							_lowercase ,		_lowercase ,		_lowercase ,		_lowercase     ):
						return len_board * len_board_column * row + column





def  a_       (							_lowercase ,		_lowercase ,		_lowercase ,		_lowercase ,		_lowercase ,		_lowercase ,		):

						if board[row][column] != word[word_index]:
												return False

						if word_index == len(_lowercase     ) - 1:
												return True

						_UpperCamelCase    :      Union[str, Any]						     =					[(0, 1), (0, -1), (-1, 0), (1, 0)]
						_UpperCamelCase    :      List[str]						     =					len(_lowercase     )
						_UpperCamelCase    :      Optional[Any]						     =					len(board[0]     )
						for direction in traverts_directions:
												_UpperCamelCase    :      Union[str, Any]						     =					row + direction[0]
												_UpperCamelCase    :      List[Any]						     =					column + direction[1]
												if not (0 <= next_i < len_board and 0 <= next_j < len_board_column):
																		continue

												_UpperCamelCase    :      Optional[Any]						     =					get_point_key(_lowercase ,		_lowercase ,		_lowercase ,		_lowercase     )
												if key in visited_points_set:
																		continue

												visited_points_set.add(_lowercase     )
												if exits_word(_lowercase ,		_lowercase ,		_lowercase ,		_lowercase ,		word_index + 1 ,		_lowercase     ):
																		return True

												visited_points_set.remove(_lowercase     )

						return False





def  a_       (							_lowercase ,		_lowercase     ):
						_UpperCamelCase    :      Optional[Any]						     =					(
						    '''The board should be a non empty matrix of single chars strings.'''
						)

						_UpperCamelCase    :      int						     =					len(_lowercase     )
						if not isinstance(_lowercase ,		_lowercase     ) or len(_lowercase     ) == 0:
												raise ValueError(_lowercase     )

						for row in board:
												if not isinstance(_lowercase ,		_lowercase     ) or len(_lowercase     ) == 0:
																		raise ValueError(_lowercase     )

												for item in row:
																		if not isinstance(_lowercase ,		_lowercase     ) or len(_lowercase     ) != 1:
																								raise ValueError(_lowercase     )

    # Validate word
						if not isinstance(_lowercase ,		_lowercase     ) or len(_lowercase     ) == 0:
												raise ValueError(
												    '''The word parameter should be a string of length greater than 0.'''     )

						_UpperCamelCase    :      List[str]						     =					len(board[0]     )
						for i in range(_lowercase     ):
												for j in range(_lowercase     ):
																		if exits_word(
																		    _lowercase ,		_lowercase ,		_lowercase ,		_lowercase ,		0 ,		{get_point_key(_lowercase ,		_lowercase ,		_lowercase ,		_lowercase     )}     ):
																								return True

						return False


if __name__ == "__main__":
						import doctest

						doctest.testmod()



