





'''simple docstring'''




import os
from typing import BinaryIO, Optional, Union

import numpy as np
import pyarrow.parquet as pq

from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MODULES
from ..packaged_modules.parquet.parquet import Parquet
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader



def    __lowerCamelCase						(      _lowercase	)   ->    Optional[int]:
							UpperCAmelCase  :	str							  =	np.inf

							def set_batch_size(_lowercase	) -> None:
														nonlocal batch_size
														if isinstance(__UpperCamelCase			,       __UpperCamelCase	):
																					UpperCAmelCase  :	List[str]							  =	min(__UpperCamelCase			,       config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS	)
														elif isinstance(__UpperCamelCase			,       __UpperCamelCase	):
																					UpperCAmelCase  :	Optional[int]							  =	min(__UpperCamelCase			,       config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS	)
														elif isinstance(__UpperCamelCase			,       __UpperCamelCase	) and feature.dtype == "binary":
																					UpperCAmelCase  :	Dict							  =	min(__UpperCamelCase			,       config.PARQUET_ROW_GROUP_SIZE_FOR_BINARY_DATASETS	)

							_visit(__UpperCamelCase			,       __UpperCamelCase	)

							return None if batch_size is np.inf else batch_size

class     UpperCamelCase_				(							__magic_name__    ):





	def __init__(						self	,	A	,	A = None	,	A = None	,	A = None	,	A = False	,	A = False	,	A = None	,	**A	,	)    ->    Any:
								super().__init__(
								    _SCREAMING_SNAKE_CASE	,	split=_SCREAMING_SNAKE_CASE	,	features=_SCREAMING_SNAKE_CASE	,	cache_dir=_SCREAMING_SNAKE_CASE	,	keep_in_memory=_SCREAMING_SNAKE_CASE	,	streaming=_SCREAMING_SNAKE_CASE	,	num_proc=_SCREAMING_SNAKE_CASE	,	**_SCREAMING_SNAKE_CASE	,	)
								UpperCAmelCase  :	str							  =	path_or_paths if isinstance(_SCREAMING_SNAKE_CASE	,	_SCREAMING_SNAKE_CASE					) else {self.split: path_or_paths}
								UpperCAmelCase  :	List[str]							  =	_PACKAGED_DATASETS_MODULES["""parquet"""][1]
								UpperCAmelCase  :	Optional[Any]							  =	Parquet(
								    cache_dir=_SCREAMING_SNAKE_CASE	,	data_files=_SCREAMING_SNAKE_CASE	,	features=_SCREAMING_SNAKE_CASE	,	hash=_SCREAMING_SNAKE_CASE	,	**_SCREAMING_SNAKE_CASE	,	)






	def 				_lowercase(						self					)    ->    Tuple:






								if self.streaming:
															UpperCAmelCase  :	Any							  =	self.builder.as_streaming_dataset(split=self.split					)
								# Build regular (map-style) dataset
								else:
															UpperCAmelCase  :	List[Any]							  =	None
															UpperCAmelCase  :	int							  =	None
															UpperCAmelCase  :	Tuple							  =	None
															UpperCAmelCase  :	List[Any]							  =	None

															self.builder.download_and_prepare(
															    download_config=_SCREAMING_SNAKE_CASE	,	download_mode=_SCREAMING_SNAKE_CASE	,	verification_mode=_SCREAMING_SNAKE_CASE	,	base_path=_SCREAMING_SNAKE_CASE	,	num_proc=self.num_proc	,	)
															UpperCAmelCase  :	str							  =	self.builder.as_dataset(
															    split=self.split	,	verification_mode=_SCREAMING_SNAKE_CASE	,	in_memory=self.keep_in_memory					)
								return dataset




class     UpperCamelCase_				:





	def __init__(						self	,	A	,	A	,	A = None	,	**A	,	)    ->    Union[str, Any]:
								UpperCAmelCase  :	int							  =	dataset
								UpperCAmelCase  :	Tuple							  =	path_or_buf
								UpperCAmelCase  :	Tuple							  =	batch_size or get_writer_batch_size(dataset.features					)
								UpperCAmelCase  :	List[Any]							  =	parquet_writer_kwargs





	def 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	int							  =	self.batch_size if self.batch_size else config.DEFAULT_MAX_BATCH_SIZE

								if isinstance(self.path_or_buf	,	(str, bytes, os.PathLike)					):
															with open(self.path_or_buf	,	"""wb+"""					) as buffer:
																						UpperCAmelCase  :	List[str]							  =	self._write(file_obj=_SCREAMING_SNAKE_CASE	,	batch_size=_SCREAMING_SNAKE_CASE	,	**self.parquet_writer_kwargs					)
								else:
															UpperCAmelCase  :	Optional[int]							  =	self._write(file_obj=self.path_or_buf	,	batch_size=_SCREAMING_SNAKE_CASE	,	**self.parquet_writer_kwargs					)
								return written






	def 				_lowercase(						self	,	A	,	A	,	**A					)    ->    int:
								UpperCAmelCase  :	List[str]							  =	0
								UpperCAmelCase  :	Dict							  =	parquet_writer_kwargs.pop("""path_or_buf"""	,	_SCREAMING_SNAKE_CASE					)
								UpperCAmelCase  :	str							  =	self.dataset.features.arrow_schema

								UpperCAmelCase  :	Dict							  =	pq.ParquetWriter(_SCREAMING_SNAKE_CASE	,	schema=_SCREAMING_SNAKE_CASE	,	**_SCREAMING_SNAKE_CASE					)

								for offset in logging.tqdm(
								    range(0	,	len(self.dataset					)	,	_SCREAMING_SNAKE_CASE					)	,	unit="""ba"""	,	disable=not logging.is_progress_bar_enabled()	,	desc="""Creating parquet from Arrow format"""	,	):
															UpperCAmelCase  :	Optional[int]							  =	query_table(
															    table=self.dataset._data	,	key=slice(_SCREAMING_SNAKE_CASE	,	offset + batch_size					)	,	indices=self.dataset._indices if self.dataset._indices is not None else None	,	)
															writer.write_table(_SCREAMING_SNAKE_CASE					)
															written += batch.nbytes
								writer.close()
								return written






'''simple docstring'''




from __future__ import annotations

from collections.abc import Sequence
from typing import Literal



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    str | Literal[False]:
							UpperCAmelCase  :	Optional[int]							  =	list(_lowercase	)
							UpperCAmelCase  :	Dict							  =	list(_lowercase	)
							UpperCAmelCase  :	str							  =	0
							for i in range(len(_lowercase	)	):
														if lista[i] != lista[i]:
																					count += 1
																					UpperCAmelCase  :	Optional[Any]							  =	"""_"""
							if count > 1:
														return False
							else:
														return "".join(_lowercase	)



def    __lowerCamelCase						(      _lowercase	)   ->    list[str]:
							UpperCAmelCase  :	List[str]							  =	[]
							while True:
														UpperCAmelCase  :	Optional[int]							  =	["""$"""] * len(_lowercase	)
														UpperCAmelCase  :	int							  =	[]
														for i in range(len(_lowercase	)	):
																					for j in range(i + 1			,       len(_lowercase	)	):
																												UpperCAmelCase  :	str							  =	compare_string(binary[i]			,       binary[j]	)
																												if k is False:
																																			UpperCAmelCase  :	Union[str, Any]							  =	"""*"""
																																			UpperCAmelCase  :	Optional[Any]							  =	"""*"""
																																			temp.append("""X"""	)
														for i in range(len(_lowercase	)	):
																					if checka[i] == "$":
																												pi.append(binary[i]	)
														if len(_lowercase	) == 0:
																					return pi
														UpperCAmelCase  :	List[Any]							  =	list(set(_lowercase	)	)



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    list[str]:
							UpperCAmelCase  :	Dict							  =	[]
							for minterm in minterms:
														UpperCAmelCase  :	List[str]							  =	""""""
														for _ in range(_lowercase	):
																					UpperCAmelCase  :	Dict							  =	str(minterm % 2	) + string
																					minterm //= 2
														temp.append(_lowercase	)
							return temp



def    __lowerCamelCase						(      _lowercase			,       _lowercase			,       _lowercase	)   ->    bool:
							UpperCAmelCase  :	Optional[int]							  =	list(_lowercase	)
							UpperCAmelCase  :	Dict							  =	list(_lowercase	)
							UpperCAmelCase  :	Dict							  =	0
							for i in range(len(_lowercase	)	):
														if lista[i] != lista[i]:
																					count_n += 1
							return count_n == count



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    list[str]:
							UpperCAmelCase  :	Tuple							  =	[]
							UpperCAmelCase  :	Optional[int]							  =	[0] * len(_lowercase	)
							for i in range(len(chart[0]	)	):
														UpperCAmelCase  :	Any							  =	0
														UpperCAmelCase  :	Optional[Any]							  =	-1
														for j in range(len(_lowercase	)	):
																					if chart[j][i] == 1:
																												count += 1
																												UpperCAmelCase  :	str							  =	j
														if count == 1:
																					UpperCAmelCase  :	Optional[int]							  =	1
							for i in range(len(_lowercase	)	):
														if select[i] == 1:
																					for j in range(len(chart[0]	)	):
																												if chart[i][j] == 1:
																																			for k in range(len(_lowercase	)	):
																																										UpperCAmelCase  :	List[str]							  =	0
																					temp.append(prime_implicants[i]	)
							while True:
														UpperCAmelCase  :	int							  =	0
														UpperCAmelCase  :	Tuple							  =	-1
														UpperCAmelCase  :	Union[str, Any]							  =	0
														for i in range(len(_lowercase	)	):
																					UpperCAmelCase  :	Optional[Any]							  =	chart[i].count(1	)
																					if count_n > max_n:
																												UpperCAmelCase  :	Union[str, Any]							  =	count_n
																												UpperCAmelCase  :	Optional[Any]							  =	i

														if max_n == 0:
																					return temp

														temp.append(prime_implicants[rem]	)

														for i in range(len(chart[0]	)	):
																					if chart[rem][i] == 1:
																												for j in range(len(_lowercase	)	):
																																			UpperCAmelCase  :	Optional[Any]							  =	0



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    list[list[int]]:
							UpperCAmelCase  :	Optional[int]							  =	[[0 for x in range(len(_lowercase	)	)] for x in range(len(_lowercase	)	)]
							for i in range(len(_lowercase	)	):
														UpperCAmelCase  :	Tuple							  =	prime_implicants[i].count("""_"""	)
														for j in range(len(_lowercase	)	):
																					if is_for_table(prime_implicants[i]			,       binary[j]			,       _lowercase	):
																												UpperCAmelCase  :	List[Any]							  =	1

							return chart



def    __lowerCamelCase						(      )   ->    None:
							UpperCAmelCase  :	str							  =	int(input("""Enter the no. of variables\n"""	)	)
							UpperCAmelCase  :	List[Any]							  =	[
							    float(_lowercase	)
							    for x in input(
							        """Enter the decimal representation of Minterms 'Spaces Separated'\n"""	).split()
							]
							UpperCAmelCase  :	str							  =	decimal_to_binary(_lowercase			,       _lowercase	)

							UpperCAmelCase  :	Tuple							  =	check(_lowercase	)
							print("""Prime Implicants are:"""	)
							print(_lowercase	)
							UpperCAmelCase  :	Union[str, Any]							  =	prime_implicant_chart(_lowercase			,       _lowercase	)

							UpperCAmelCase  :	Tuple							  =	selection(_lowercase			,       _lowercase	)
							print("""Essential Prime Implicants are:"""	)
							print(_lowercase	)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()

