
"""simple docstring"""
def    _lowerCAmelCase    (     lowerCamelCase__							:							list[list]				)  ->    list[list]:
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = current_set.copy()
  for row_index, row in enumerate(lowerCamelCase__				):
    _SCREAMING_SNAKE_CASE   :				Any							    = row[0]
    for column_index, column in enumerate(lowerCamelCase__				):
      if magnitude == 0:
        _SCREAMING_SNAKE_CASE   :				Optional[int]							    = column
        continue
      _SCREAMING_SNAKE_CASE   :				int							    = column / magnitude
    # Subtract to cancel term
  _SCREAMING_SNAKE_CASE   :				List[Any]							    = current_set[0]
  _SCREAMING_SNAKE_CASE   :				Tuple							    = [first_row]
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = current_set[1::]
  for row in current_set:
    _SCREAMING_SNAKE_CASE   :				List[str]							    = []
    # If first term is 0, it is already in form we want, so we preserve it
    if row[0] == 0:
      final_set.append(lowerCamelCase__				)
      continue
    for column_index in range(len(lowerCamelCase__				)				):
      temp_row.append(first_row[column_index] - row[column_index]				)
    final_set.append(lowerCamelCase__				)
  # Create next recursion iteration set
  if len(final_set[0]				) != 3:
    _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = final_set[0]
    _SCREAMING_SNAKE_CASE   :				int							    = []
    _SCREAMING_SNAKE_CASE   :				Any							    = []
    for row in final_set[1::]:
      current_first_column.append(row[0]				)
      next_iteration.append(row[1::]				)
    _SCREAMING_SNAKE_CASE   :				Optional[int]							    = simplify(lowerCamelCase__				)
    for i in range(len(lowerCamelCase__				)				):
      resultant[i].insert(0,						current_first_column[i]				)
    resultant.insert(0,						lowerCamelCase__				)
    _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = resultant
  return final_set





def    _lowerCAmelCase    (     lowerCamelCase__							:							list[list]				)  ->    list:
  if len(lowerCamelCase__				) == 0:
    raise IndexError("solve_simultaneous() requires n lists of length n+1"				)
  _SCREAMING_SNAKE_CASE   :				int							    = len(lowerCamelCase__				) + 1
  if any(len(lowerCamelCase__				) != _length for item in equations				):
    raise IndexError("solve_simultaneous() requires n lists of length n+1"				)
  for row in equations:
    if any(not isinstance(lowerCamelCase__,						(int, float)				) for column in row				):
      raise ValueError("solve_simultaneous() requires lists of integers"				)
  if len(lowerCamelCase__				) == 1:
    return [equations[0][-1] / equations[0][0]]
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = equations.copy()
  if any(0 in row for row in data_set				):
    _SCREAMING_SNAKE_CASE   :				Dict							    = data_set.copy()
    _SCREAMING_SNAKE_CASE   :				int							    = []
    for row_index, row in enumerate(lowerCamelCase__				):
      if 0 not in row:
        _SCREAMING_SNAKE_CASE   :				str							    = data_set.pop(lowerCamelCase__				)
        break
    if not full_row:
      raise ValueError("solve_simultaneous() requires at least 1 full equation"				)
    data_set.insert(0,						lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				List[str]							    = data_set.copy()
  _SCREAMING_SNAKE_CASE   :				Dict							    = simplify(lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				Dict							    = simplified[::-1]
  _SCREAMING_SNAKE_CASE   :				list							    = []
  for row in simplified:
    _SCREAMING_SNAKE_CASE   :				Dict							    = row[-1]
    if not solutions:
      if row[-2] == 0:
        solutions.append(0				)
        continue
      solutions.append(current_solution / row[-2]				)
      continue
    _SCREAMING_SNAKE_CASE   :				str							    = row.copy()[: len(lowerCamelCase__				) - 1 :]
    while temp_row[0] == 0:
      temp_row.pop(0				)
    if len(lowerCamelCase__				) == 0:
      solutions.append(0				)
      continue
    _SCREAMING_SNAKE_CASE   :				List[Any]							    = temp_row[1::]
    _SCREAMING_SNAKE_CASE   :				str							    = temp_row[::-1]
    for column_index, column in enumerate(lowerCamelCase__				):
      current_solution -= column * solutions[column_index]
    solutions.append(lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = []
  for item in solutions:
    final.append(float(round(lowerCamelCase__,						5				)				)				)
  return final[::-1]


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      lowercase_       :						Optional[int]     					=	[
          [2, 1, 1, 1, 1, 4],
          [1, 2, 1, 1, 1, 5],
          [1, 1, 2, 1, 1, 6],
          [1, 1, 1, 2, 1, 7],
          [1, 1, 1, 1, 2, 8],
      ]
      print(solve_simultaneous(eq))
      print(solve_simultaneous([[4, 2]]))





"""simple docstring"""
import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer





def    _lowerCAmelCase    (     lowerCamelCase__							:							Any,						lowerCamelCase__							:							Optional[Any],						lowerCamelCase__							:							List[str],						lowerCamelCase__							:							Any=1_0_2_4				)  ->    Optional[int]:
  _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				int							    = [], []

  _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = list(zip(lowerCamelCase__,						lowerCamelCase__				)				)
  _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				List[Any]							    = sorted_examples[0]

  def is_too_big(lowerCamelCase__							:							List[Any]				):
    return tok(lowerCamelCase__,						return_tensors="pt"				).input_ids.shape[1] > max_tokens

  for src, tgt in tqdm(sorted_examples[1:]				):
    _SCREAMING_SNAKE_CASE   :				int							    = new_src + " " + src
    _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = new_tgt + " " + tgt
    if is_too_big(lowerCamelCase__				) or is_too_big(lowerCamelCase__				):  # cant fit, finalize example
      finished_src.append(lowerCamelCase__				)
      finished_tgt.append(lowerCamelCase__				)
      _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Any							    = src, tgt
    else:  # can fit, keep adding
      _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Optional[Any]							    = cand_src, cand_tgt

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





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





def    _lowerCAmelCase    (     )  ->    int:
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = argparse.ArgumentParser()
  parser.add_argument("--tok_name",						type=lowerCamelCase__,						help="like facebook/bart-large-cnn,t5-base, etc."				)
  parser.add_argument("--max_seq_len",						type=lowerCamelCase__,						default=1_2_8				)
  parser.add_argument("--data_dir",						type=lowerCamelCase__				)
  parser.add_argument("--save_path",						type=lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				Tuple							    = parser.parse_args()
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = AutoTokenizer.from_pretrained(args.tok_name				)
  return pack_data_dir(lowerCamelCase__,						Path(args.data_dir				),						args.max_seq_len,						args.save_path				)


if __name__ == "__main__":
      packer_cli()



