





import argparse
from collections import defaultdict

def     a_       (					lowerCAmelCase_ :     Optional[int],      lowerCAmelCase_ :     Optional[int],      lowerCAmelCase_ :     str,      lowerCAmelCase_ :     int,      lowerCAmelCase_ :     List[str]      ):
   __lowerCAmelCase				      =      F"""{file}_{class_name}_{test_name}"""
   done_test[_id] += 1

   with open(lowerCAmelCase_,      'r'      ) as f:
      __lowerCAmelCase				      =      f.readlines()

   __lowerCAmelCase				      =      F"""class {class_name}("""
   __lowerCAmelCase				      =      F"""{4 * " "}def {test_name}("""
   __lowerCAmelCase				      =      F"""{8 * " "}{correct_line.split()[0]}"""
   __lowerCAmelCase				      =      F"""{16 * " "}{correct_line.split()[0]}"""
   __lowerCAmelCase				      =      False
   __lowerCAmelCase				      =      False
   __lowerCAmelCase				      =      False
   __lowerCAmelCase				      =      False
   __lowerCAmelCase				      =      0
   __lowerCAmelCase				      =      0

   __lowerCAmelCase				      =      []
   for line in lines:
      if line.startswith(lowerCAmelCase_      ):
         __lowerCAmelCase				      =      True
      elif in_class and line.startswith(lowerCAmelCase_      ):
         __lowerCAmelCase				      =      True
      elif in_class and in_func and (line.startswith(lowerCAmelCase_      ) or line.startswith(lowerCAmelCase_      )):
         __lowerCAmelCase				      =      len(line.split(correct_line.split()[0]      )[0]      )
         count += 1

         if count == done_test[_id]:
            __lowerCAmelCase				      =      True

      if in_class and in_func and in_line:
         if ")" not in line:
            continue
         else:
            __lowerCAmelCase				      =      True

      if in_class and in_func and in_line and insert_line:
         new_lines.append(F"""{spaces * " "}{correct_line}"""      )
         __lowerCAmelCase				      =      __lowerCAmelCase				      =      __lowerCAmelCase				      =      __lowerCAmelCase				      =      False
      else:
         new_lines.append(lowerCAmelCase_      )

   with open(lowerCAmelCase_,      'w'      ) as f:
      for line in new_lines:
         f.write(lowerCAmelCase_      )

def     a_       (					lowerCAmelCase_ :     Tuple,      lowerCAmelCase_ :     Any=None      ):
   if fail is not None:
      with open(lowerCAmelCase_,      'r'      ) as f:
         __lowerCAmelCase				      =      {l.strip() for l in f.readlines()}
   else:
      __lowerCAmelCase				      =      None

   with open(lowerCAmelCase_,      'r'      ) as f:
      __lowerCAmelCase				      =      f.readlines()

   __lowerCAmelCase				      =      defaultdict(lowerCAmelCase_      )
   for line in correct_lines:
      __lowerCAmelCase      ,      __lowerCAmelCase      ,      __lowerCAmelCase      ,      __lowerCAmelCase				      =      line.split(';'      )
      if test_failures is None or "::".join([file, class_name, test_name]      ) in test_failures:
         overwrite_file(lowerCAmelCase_,      lowerCAmelCase_,      lowerCAmelCase_,      lowerCAmelCase_,      lowerCAmelCase_      )


if __name__ == "__main__":
     _snake_case    :       List[str]		       =    argparse.ArgumentParser()
     parser.add_argument('--correct_filename', help='filename of tests with expected result')
     parser.add_argument('--fail_filename', help='filename of test failures', type=str, default=None)
     _snake_case    :       str		       =    parser.parse_args()

     main(args.correct_filename, args.fail_filename)




"""simple docstring"""
import unittest

import numpy as np
import torch

from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad

class       lowerCamelCase	(       unittest.TestCase   ):


  '''simple docstring'''







  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							List[str]							=    10



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							List[str]							=    [1, 2, 3, 4]
        UpperCAmelCase__			:							Tuple							=    [1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
        self.assertEqual(truncate_or_pad(_lowerCamelCase							,       self.block_size							,       0	)							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[int]							=    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
        UpperCAmelCase__			:							Tuple							=    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
        self.assertEqual(truncate_or_pad(_lowerCamelCase							,       self.block_size							,       0	)							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Tuple							=    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
        UpperCAmelCase__			:							Dict							=    [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
        self.assertEqual(truncate_or_pad(_lowerCamelCase							,       self.block_size							,       0	)							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Any							=    """It was the year of Our Lord one thousand seven hundred and
        seventy-five.\n\nSpiritual revelations were conceded to England at that
        favoured period, as at this."""
        UpperCAmelCase__					,		UpperCAmelCase__			:							Any							=    process_story(_lowerCamelCase	)
        self.assertEqual(_lowerCamelCase							,       []	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							str							=    """"""
        UpperCAmelCase__					,		UpperCAmelCase__			:							List[Any]							=    process_story(_lowerCamelCase	)
        self.assertEqual(_lowerCamelCase							,       []	)
        self.assertEqual(_lowerCamelCase							,       []	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[Any]							=    (
            """It was the year of Our Lord one thousand seven hundred and """
            """seventy-five\n\nSpiritual revelations were conceded to England """
            """at that favoured period, as at this.\n@highlight\n\nIt was the best of times"""
        )
        UpperCAmelCase__					,		UpperCAmelCase__			:							Optional[Any]							=    process_story(_lowerCamelCase	)

        UpperCAmelCase__			:							List[Any]							=    [
            """It was the year of Our Lord one thousand seven hundred and seventy-five.""",
            """Spiritual revelations were conceded to England at that favoured period, as at this.""",
        ]
        self.assertEqual(_lowerCamelCase							,       _lowerCamelCase	)

        UpperCAmelCase__			:							List[Any]							=    ["""It was the best of times."""]
        self.assertEqual(_lowerCamelCase							,       _lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							str							=    torch.tensor([1, 2, 3, 4]	)
        UpperCAmelCase__			:							str							=    torch.tensor([1, 1, 1, 1]	)
        np.testing.assert_array_equal(build_mask(_lowerCamelCase							,       0	).numpy()							,       expected.numpy()	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							List[str]							=    torch.tensor([1, 2, 3, 4, 23, 23, 23]	)
        UpperCAmelCase__			:							Union[str, Any]							=    torch.tensor([1, 1, 1, 1, 0, 0, 0]	)
        np.testing.assert_array_equal(build_mask(_lowerCamelCase							,       23	).numpy()							,       expected.numpy()	)



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Optional[Any]							=    torch.tensor([8, 2, 3, 4, 1, 1, 1]	)
        UpperCAmelCase__			:							Any							=    torch.tensor([1, 1, 1, 1, 0, 0, 0]	)
        np.testing.assert_array_equal(build_mask(_lowerCamelCase							,       1	).numpy()							,       expected.numpy()	)




  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							Any							=    101
        UpperCAmelCase__			:							Dict							=    torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 101, 5, 6], [1, 101, 3, 4, 101, 6]]	)
        UpperCAmelCase__			:							Optional[Any]							=    torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]	)

        UpperCAmelCase__			:							int							=    compute_token_type_ids(_lowerCamelCase							,       _lowerCamelCase	)
        np.testing.assert_array_equal(_lowerCamelCase							,       _lowerCamelCase	)

