






"""simple docstring"""




import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer

def 			lowerCAmelCase__     (     UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__=1_0_2_4				):



  '''simple docstring'''
  _a      ,  _a  :       Any             =	[], []

  _a  :       str             =	list(zip(UpperCamelCase__     ,   UpperCamelCase__				)				)
  _a      ,  _a  :       Tuple             =	sorted_examples[0]

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

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

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

def 			lowerCAmelCase__     (     UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__				):



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

def 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       Union[str, Any]             =	argparse.ArgumentParser()
  parser.add_argument("""--tok_name"""     ,   type=UpperCamelCase__     ,   help="""like facebook/bart-large-cnn,t5-base, etc."""				)
  parser.add_argument("""--max_seq_len"""     ,   type=UpperCamelCase__     ,   default=1_2_8				)
  parser.add_argument("""--data_dir"""     ,   type=UpperCamelCase__				)
  parser.add_argument("""--save_path"""     ,   type=UpperCamelCase__				)
  _a  :       int             =	parser.parse_args()
  _a  :       int             =	AutoTokenizer.from_pretrained(args.tok_name				)
  return pack_data_dir(UpperCamelCase__     ,   Path(args.data_dir				)     ,   args.max_seq_len     ,   args.save_path				)


if __name__ == "__main__":
 packer_cli()









"""simple docstring"""




import unittest

import numpy as np

def 			lowerCAmelCase__     (     UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__ = None     ,   ):



  '''simple docstring'''
  _a  :       List[Any]             =	np.shape(UpperCamelCase__				)
  _a  :       Any             =	np.shape(UpperCamelCase__				)
  _a  :       Union[str, Any]             =	np.shape(UpperCamelCase__				)

  if shape_a[0] != shape_b[0]:
    _a  :       int             =	(
        """Expected the same number of rows for A and B. """
        F"""Instead found A of size {shape_a} and B of size {shape_b}"""
    )
    raise ValueError(UpperCamelCase__				)

  if shape_b[1] != shape_c[1]:
    _a  :       Tuple             =	(
        """Expected the same number of columns for B and C. """
        F"""Instead found B of size {shape_b} and C of size {shape_c}"""
    )
    raise ValueError(UpperCamelCase__				)

  _a  :       int             =	pseudo_inv
  if a_inv is None:
    try:
      _a  :       Optional[int]             =	np.linalg.inv(UpperCamelCase__				)
    except np.linalg.LinAlgError:
      raise ValueError(
          """Input matrix A is not invertible. Cannot compute Schur complement."""				)

  return mat_c - mat_b.T @ a_inv @ mat_b






class        UpperCamelCase			(	unittest.TestCase      ):


 def _lowercase	(     self		:						int							)					->       None:
   _a  :       str             =	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
   _a  :       Tuple             =	np.array([[0, 3], [3, 0], [2, 3]]							)
   _a  :       Optional[int]             =	np.array([[2, 1], [6, 3]]							)

   _a  :       Optional[Any]             =	schur_complement(UpperCAmelCase__							,						UpperCAmelCase__							,						UpperCAmelCase__							)

   _a  :       Union[str, Any]             =	np.block([[a, b], [b.T, c]]							)

   _a  :       int             =	np.linalg.det(UpperCAmelCase__							)
   _a  :       Union[str, Any]             =	np.linalg.det(UpperCAmelCase__							)
   _a  :       List[Any]             =	np.linalg.det(UpperCAmelCase__							)

   self.assertAlmostEqual(UpperCAmelCase__							,						det_a * det_s							)


 def _lowercase	(     self		:						int							)					->       None:
   _a  :       Optional[int]             =	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
   _a  :       Optional[int]             =	np.array([[0, 3], [3, 0], [2, 3]]							)
   _a  :       Union[str, Any]             =	np.array([[2, 1], [6, 3]]							)

   with self.assertRaises(UpperCAmelCase__							):
     schur_complement(UpperCAmelCase__							,						UpperCAmelCase__							,						UpperCAmelCase__							)







 def _lowercase	(     self		:						List[Any]							)					->       None:
   _a  :       Any             =	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
   _a  :       Dict             =	np.array([[0, 3], [3, 0], [2, 3]]							)
   _a  :       List[Any]             =	np.array([[2, 1, 3], [6, 3, 5]]							)

   with self.assertRaises(UpperCAmelCase__							):
     schur_complement(UpperCAmelCase__							,						UpperCAmelCase__							,						UpperCAmelCase__							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 unittest.main()

