





'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


a   	=    logging.get_logger(__name__)







class __a			( _snake_case      ):





   def __init__(       self					:      Tuple					,*lowerCamelCase					:      Optional[int]					,**lowerCamelCase					:      Union[str, Any]     ):

      '''simple docstring'''

      warnings.warn(
          """The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
          """ Please use ImageGPTImageProcessor instead."""					,lowerCamelCase					,)
      super().__init__(*lowerCamelCase					,**lowerCamelCase     )











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


__UpperCamelCase   :			str          = generate_large_matrix()
__UpperCamelCase   :			Tuple          = (
    [[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						(      __lowerCamelCase       ) ->			None:
	assert all(row == sorted(__lowerCamelCase				,     reverse=__lowerCamelCase       ) for row in grid       )
	assert all(list(__lowerCamelCase       ) == sorted(__lowerCamelCase				,     reverse=__lowerCamelCase       ) for col in zip(*__lowerCamelCase       )       )





def 						__A						(      __lowerCamelCase       ) ->			int:
	a									=				0
	a									=				len(__lowerCamelCase       ) - 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(__lowerCamelCase       )





def 						__A						(      __lowerCamelCase       ) ->			int:
	a									=				0
	a									=				len(grid[0]       )

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





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





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





def 						__A						(      ) ->			None:
	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=__lowerCamelCase				,     number=500       )
		print(f'{func}() took {time:0.4f} seconds'       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()

