


def  _a			(						):
     return [list(range(1_0_0_0 - i  ,  -1_0_0_0 - i  ,  -1 ) ) for i in range(1_0_0_0 )]


__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  _a			(						__UpperCamelCase ):
     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  _a			(						__UpperCamelCase ):
     a_    :     Optional[int]										=    0
     a_    :     Optional[Any]										=    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:
          a_    :     Optional[int]										=    (left + right) // 2
          a_    :     int										=    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:
               a_    :     Optional[int]										=    mid + 1
          else:
               a_    :     int										=    mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
     return len(__UpperCamelCase )



def  _a			(						__UpperCamelCase ):
     a_    :     int										=    0
     a_    :     Dict										=    len(grid[0] )

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



def  _a			(						__UpperCamelCase ):
     return len([number for row in grid for number in row if number < 0] )



def  _a			(						__UpperCamelCase ):
     a_    :     Dict										=    0
     for row in grid:
          for i, number in enumerate(__UpperCamelCase ):
               if number < 0:
                    total += len(__UpperCamelCase ) - i
                    break
     return total



def  _a			(						):
     from timeit import timeit

     print("""Running benchmarks""" )
     a_    :     Tuple										=    (
         """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
     ):
          a_    :     List[Any]										=    timeit(F'''{func}(grid=grid)'''  ,  setup=__UpperCamelCase  ,  number=5_0_0 )
          print(F'''{func}() took {time:0.4f} seconds''' )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       benchmark()






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__lowerCamelCase        =     {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTConfig''', '''ViTOnnxConfig''']}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     ['''ViTFeatureExtractor''']
       __lowerCamelCase        =     ['''ViTImageProcessor''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''VIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''ViTForImageClassification''',
           '''ViTForMaskedImageModeling''',
           '''ViTModel''',
           '''ViTPreTrainedModel''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''TFViTForImageClassification''',
           '''TFViTModel''',
           '''TFViTPreTrainedModel''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''FlaxViTForImageClassification''',
           '''FlaxViTModel''',
           '''FlaxViTPreTrainedModel''',
       ]

if TYPE_CHECKING:
       from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_vit import ViTFeatureExtractor
              from .image_processing_vit import ViTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vit import (
                  VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ViTForImageClassification,
                  ViTForMaskedImageModeling,
                  ViTModel,
                  ViTPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
       import sys

       __lowerCamelCase        =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



