
"""simple docstring"""


import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer






def 					_snake_case (						snake_case__      :   Tuple		,					snake_case__      :   Dict		,					snake_case__      :   Tuple		,					snake_case__      :   Optional[int]=1024   ):
	A      ,					A        =      [], []

	A        =      list(zip(snake_case__		,					snake_case__   )   )
	A      ,					A        =      sorted_examples[0]

	def is_too_big(snake_case__      :   Optional[int]   ):
		return tok(snake_case__		,					return_tensors='pt'   ).input_ids.shape[1] > max_tokens

	for src, tgt in tqdm(sorted_examples[1:]   ):
		A        =      new_src + ' ' + src
		A        =      new_tgt + ' ' + tgt
		if is_too_big(snake_case__   ) or is_too_big(snake_case__   ):  # cant fit, finalize example
			finished_src.append(snake_case__   )
			finished_tgt.append(snake_case__   )
			A      ,					A        =      src, tgt
		else:  # can fit, keep adding
			A      ,					A        =      cand_src, cand_tgt

    # cleanup
	if new_src:
		assert new_tgt
		finished_src.append(snake_case__   )
		finished_tgt.append(snake_case__   )
	return finished_src, finished_tgt






def 					_snake_case (						snake_case__      :   Tuple		,					snake_case__      :   Optional[Any]		,					snake_case__      :   Any		,					snake_case__      :   List[str]   ):
	A        =      Path(snake_case__   )
	save_path.mkdir(exist_ok=snake_case__   )
	for split in ["train"]:
		A      ,					A        =      data_dir / F'{split}.source', data_dir / F'{split}.target'
		A        =      [x.rstrip() for x in Path(snake_case__   ).open().readlines()]
		A        =      [x.rstrip() for x in Path(snake_case__   ).open().readlines()]
		A      ,					A        =      pack_examples(snake_case__		,					snake_case__		,					snake_case__		,					snake_case__   )
		print(F'packed {split} split from {len(snake_case__   )} examples -> {len(snake_case__   )}.'   )
		Path(save_path / F'{split}.source'   ).open('w'   ).write('\n'.join(snake_case__   )   )
		Path(save_path / F'{split}.target'   ).open('w'   ).write('\n'.join(snake_case__   )   )
	for split in ["val", "test"]:
		A      ,					A        =      data_dir / F'{split}.source', data_dir / F'{split}.target'
		shutil.copyfile(snake_case__		,					save_path / F'{split}.source'   )
		shutil.copyfile(snake_case__		,					save_path / F'{split}.target'   )






def 					_snake_case (						):
	A        =      argparse.ArgumentParser()
	parser.add_argument('--tok_name'		,					type=snake_case__		,					help='like facebook/bart-large-cnn,t5-base, etc.'   )
	parser.add_argument('--max_seq_len'		,					type=snake_case__		,					default=128   )
	parser.add_argument('--data_dir'		,					type=snake_case__   )
	parser.add_argument('--save_path'		,					type=snake_case__   )
	A        =      parser.parse_args()
	A        =      AutoTokenizer.from_pretrained(args.tok_name   )
	return pack_data_dir(snake_case__		,					Path(args.data_dir   )		,					args.max_seq_len		,					args.save_path   )


if __name__ == "__main__":
		packer_cli()
"""simple docstring"""






import math



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				if (
				    not isinstance(lowerCamelCase					,			(int, float)       )
				    or power_factor < -1
				    or power_factor > 1
				):
								raise ValueError('power_factor must be a valid float value between -1 and 1.'       )
				return apparent_power * power_factor



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				if (
				    not isinstance(lowerCamelCase					,			(int, float)       )
				    or power_factor < -1
				    or power_factor > 1
				):
								raise ValueError('power_factor must be a valid float value between -1 and 1.'       )
				return apparent_power * math.sqrt(1 - power_factor**2       )


if __name__ == "__main__":
						import doctest

						doctest.testmod()



