




def SCREAMING_SNAKE_CASE    (	)       ->	list[list[int]]:



    """simple docstring"""

    return [list(range(1_000 - i			,    -1_000 - i			,    -1						)						) for i in range(1_000						)]


_lowerCamelCase     :		Any								=       generate_large_matrix()
_lowerCamelCase     :		List[str]								=       (
    [[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 SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



    """simple docstring"""

    assert all(row == sorted(lowercase_			,    reverse=lowercase_						) for row in grid						)
    assert all(list(lowercase_						) == sorted(lowercase_			,    reverse=lowercase_						) for col in zip(*lowercase_						)						)







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	int:



    """simple docstring"""

    A__							=   0
    A__							=   len(lowercase_						) - 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__							=   (left + right) // 2
        A__							=   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__							=   mid + 1
        else:
            A__							=   mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
    return len(lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	int:



    """simple docstring"""

    A__							=   0
    A__							=   len(grid[0]						)

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







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	int:



    """simple docstring"""

    return len([number for row in grid for number in row if number < 0]						)







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	int:



    """simple docstring"""

    A__							=   0
    for row in grid:
        for i, number in enumerate(lowercase_						):
            if number < 0:
                total += len(lowercase_						) - i
                break
    return total







def SCREAMING_SNAKE_CASE    (	)       ->	None:



    """simple docstring"""

    from timeit import timeit

    print('''Running benchmarks'''						)
    A__							=   (
        '''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__							=   timeit(f"""{func}(grid=grid)"""			,    setup=lowercase_			,    number=500						)
        print(f"""{func}() took {time:0.4f} seconds"""						)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  benchmark()








from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase     :		str								=       {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Dict								=       [
      """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """FocalNetForImageClassification""",
      """FocalNetForMaskedImageModeling""",
      """FocalNetBackbone""",
      """FocalNetModel""",
      """FocalNetPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_focalnet import (
        FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        FocalNetBackbone,
        FocalNetForImageClassification,
        FocalNetForMaskedImageModeling,
        FocalNetModel,
        FocalNetPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase     :		Tuple								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


