


'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa

import datasets
from datasets.table import table_cast


__magic_name__   :   int  							=datasets.utils.logging.get_logger(__name__)






@dataclass
class 		UpperCamelCase_		(					datasets.BuilderConfig   ):





						"""simple docstring"""




						UpperCAmelCase__	:       List[Any]         =     None






class 		UpperCamelCase_		(					datasets.ArrowBasedBuilder   ):





						"""simple docstring"""




						UpperCAmelCase__	:       str         =     ArrowConfig
						def 					__A					( self				:					List[str]  )							->					int:
										return datasets.DatasetInfo(features=self.config.features  )
						def 					__A					( self				:					Union[str, Any]	,				_lowerCamelCase				:					Dict  )							->					int:





										if not self.config.data_files:
														raise ValueError(f'At least one data file must be specified, but got data_files={self.config.data_files}'  )
										__magic_name__	  = dl_manager.download_and_extract(self.config.data_files  )
										if isinstance(__a	,				(str, list, tuple)  ):
														__magic_name__	  = data_files
														if isinstance(__a	,				__a  ):
																		__magic_name__	  = [files]
														# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
														__magic_name__	  = [dl_manager.iter_files(__a  ) for file in files]
														return [datasets.SplitGenerator(name=datasets.Split.TRAIN	,				gen_kwargs={"files": files}  )]
										__magic_name__	  = []
										for split_name, files in data_files.items():
														if isinstance(__a	,				__a  ):
																		__magic_name__	  = [files]
														# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
														__magic_name__	  = [dl_manager.iter_files(__a  ) for file in files]
														# Infer features is they are stoed in the arrow schema
														if self.info.features is None:
																		for file in itertools.chain.from_iterable(__a  ):
																						with open(__a	,				"rb"  ) as f:
																										__magic_name__	  = datasets.Features.from_arrow_schema(pa.ipc.open_stream(__a  ).schema  )
																						break
														splits.append(datasets.SplitGenerator(name=__a	,				gen_kwargs={"files": files}  )  )
										return splits
						def 					__A					( self				:					Tuple	,				_lowerCamelCase				:					Optional[int]  )							->					str:





										if self.info.features is not None:
														# more expensive cast to support nested features with keys in a different order
														# allows str <-> int/float or str to Audio for example
														__magic_name__	  = table_cast(__a	,				self.info.features.arrow_schema  )
										return pa_table

						def 					__A					( self				:					str	,				_lowerCamelCase				:					Tuple  )							->					Any:





										for file_idx, file in enumerate(itertools.chain.from_iterable(__a  )  ):
														with open(__a	,				"rb"  ) as f:
																		try:
																						for batch_idx, record_batch in enumerate(pa.ipc.open_stream(__a  )  ):
																										__magic_name__	  = pa.Table.from_batches([record_batch]  )
																										# Uncomment for debugging (will print the Arrow table size and elements)
																										# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																										# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																										yield f'{file_idx}_{batch_idx}', self._cast_table(__a  )
																		except ValueError as e:
																						logger.error(f'Failed to read file \'{file}\' with error {type(__a  )}: {e}'  )
																						raise







'''simple docstring'''
import numpy as np

__magic_name__   :   str  							=[
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]






class 		UpperCamelCase_		:





						"""simple docstring"""




						def __init__( self				:					Union[str, Any]  )							->					None:
										__magic_name__	  = np.array(_lowerCamelCase  )
						def 					__A					( self				:					List[str]	,				_lowerCamelCase				:					str  )							->					np.ndarray:
										__magic_name__  ,      __magic_name__	  = np.where(letter == self.SQUARE  )
										__magic_name__	  = np.concatenate([indexa + 1, indexa + 1]  )
										return indexes
						def 					__A					( self				:					Any	,				_lowerCamelCase				:					int	,				_lowerCamelCase				:					int  )							->					str:
										return self.SQUARE[indexa - 1, indexa - 1]
						def 					__A					( self				:					Union[str, Any]	,				_lowerCamelCase				:					str  )							->					str:
										__magic_name__	  = message.lower()
										__magic_name__	  = message.replace("j"	,				"i"  )

										__magic_name__	  = ""
										for letter_index in range(len(_lowerCamelCase  )  ):
														if message[letter_index] != " ":
																		__magic_name__	  = self.letter_to_numbers(message[letter_index]  )
																		__magic_name__	  = encoded_message + str(numbers[0]  ) + str(numbers[1]  )
														elif message[letter_index] == " ":
																		__magic_name__	  = encoded_message + " "

										return encoded_message

						def 					__A					( self				:					Optional[Any]	,				_lowerCamelCase				:					str  )							->					str:
										__magic_name__	  = message.replace(" "	,				"  "  )
										__magic_name__	  = ""
										for numbers_index in range(int(len(_lowerCamelCase  ) / 2  )  ):
														if message[numbers_index * 2] != " ":
																		__magic_name__	  = message[numbers_index * 2]
																		__magic_name__	  = message[numbers_index * 2 + 1]

																		__magic_name__	  = self.numbers_to_letter(int(_lowerCamelCase  )	,				int(_lowerCamelCase  )  )
																		__magic_name__	  = decoded_message + letter
														elif message[numbers_index * 2] == " ":
																		__magic_name__	  = decoded_message + " "

										return decoded_message



