

"""simple docstring"""






def 	lowercase      (   ) ->      list[list[int]]:
 return [list(range(1000 - i      ,   -1000 - i      ,   -1						)						) for i in range(1000						)]


__lowerCamelCase										=		generate_large_matrix()
__lowerCamelCase										=		(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)





def 	lowercase      (   __UpperCamelCase						) ->      None:
 assert all(row == sorted(__UpperCamelCase      ,   reverse=__UpperCamelCase						) for row in grid						)
 assert all(list(__UpperCamelCase						) == sorted(__UpperCamelCase      ,   reverse=__UpperCamelCase						) for col in zip(*__UpperCamelCase						)						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 __magic_name__     =      0
 __magic_name__     =      len(__UpperCamelCase						) - 1

 # Edge cases such as no values or all numbers are negative.
 if not array or array[0] < 0:
  return 0

 while right + 1 > left:
  __magic_name__     =      (left + right) // 2
  __magic_name__     =      array[mid]

  # Num must be negative and the index must be greater than or equal to 0.
  if num < 0 and array[mid - 1] >= 0:
   return mid

  if num >= 0:
   __magic_name__     =      mid + 1
  else:
   __magic_name__     =      mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
 return len(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 __magic_name__     =      0
 __magic_name__     =      len(grid[0]						)

 for i in range(len(__UpperCamelCase						)						):
  __magic_name__     =      find_negative_index(grid[i][:bound]						)
  total += bound
 return (len(__UpperCamelCase						) * len(grid[0]						)) - total





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return len([number for row in grid for number in row if number < 0]						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 __magic_name__     =      0
 for row in grid:
  for i, number in enumerate(__UpperCamelCase						):
   if number < 0:
    total += len(__UpperCamelCase						) - i
    break
 return total





def 	lowercase      (   ) ->      None:
 from timeit import timeit

 print('''Running benchmarks'''						)
 __magic_name__     =      (
     '''from __main__ import count_negatives_binary_search, '''
     '''count_negatives_brute_force, count_negatives_brute_force_with_break, grid'''
 )
 for func in (
     "count_negatives_binary_search",  # took 0.7727 seconds
     "count_negatives_brute_force_with_break",  # took 4.6505 seconds
     "count_negatives_brute_force",  # took 12.8160 seconds
 ):
  __magic_name__     =      timeit(f'''{func}(grid=grid)'''      ,   setup=__UpperCamelCase      ,   number=500						)
  print(f'''{func}() took {time:0.4f} seconds'''						)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    benchmark()




"""simple docstring"""






import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
 from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require_tokenizers
class        _lowercase					(     unittest.TestCase     ):







     @slow
     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small''' ,						return_dict=UpperCamelCase_       ).to(UpperCamelCase_       )
      __magic_name__     =      AutoTokenizer.from_pretrained('''google/mt5-small'''       )

      __magic_name__     =      tokenizer('''Hello there''' ,						return_tensors='''pt'''       ).input_ids
      __magic_name__     =      tokenizer('''Hi I am''' ,						return_tensors='''pt'''       ).input_ids

      __magic_name__     =      model(input_ids.to(UpperCamelCase_       ) ,						labels=labels.to(UpperCamelCase_       )       ).loss
      __magic_name__     =      -(labels.shape[-1] * loss.item())

      __magic_name__     =      -8_4.9_1_2_7
      self.assertTrue(abs(mtf_score - EXPECTED_SCORE       ) < 1E-4       )

