


'''simple docstring'''



from __future__ import annotations


def    lowerCamelCase__   ( A     :    tuple[int, int]   ,     A     :    int  ):




						'''simple docstring'''






						UpperCAmelCase       ,       UpperCAmelCase         =			position
						UpperCAmelCase         =			[
						    (y + 1, x + 2),
						    (y - 1, x + 2),
						    (y + 1, x - 2),
						    (y - 1, x - 2),
						    (y + 2, x + 1),
						    (y + 2, x - 1),
						    (y - 2, x + 1),
						    (y - 2, x - 1),
						]
						UpperCAmelCase         =			[]

						for position in positions:
												UpperCAmelCase       ,       UpperCAmelCase         =			position
												if 0 <= y_test < n and 0 <= x_test < n:
																		permissible_positions.append(A  )

						return permissible_positions


def    lowerCamelCase__   ( A     :    list[list[int]]  ):




						'''simple docstring'''






						return not any(elem == 0 for row in board for elem in row  )


def    lowerCamelCase__   ( A     :    list[list[int]]   ,     A     :    tuple[int, int]   ,     A     :    int  ):




						'''simple docstring'''






						if is_complete(A  ):
												return True

						for position in get_valid_pos(A   ,     len(A  )  ):
												UpperCAmelCase       ,       UpperCAmelCase         =			position

												if board[y][x] == 0:
																		UpperCAmelCase         =			curr + 1
																		if open_knight_tour_helper(A   ,     A   ,     curr + 1  ):
																								return True
																		UpperCAmelCase         =			0

						return False


def    lowerCamelCase__   ( A     :    int  ):




						'''simple docstring'''






						UpperCAmelCase         =			[[0 for i in range(A  )] for j in range(A  )]

						for i in range(A  ):
												for j in range(A  ):
																		UpperCAmelCase         =			1
																		if open_knight_tour_helper(A   ,     (i, j)   ,     1  ):
																								return board
																		UpperCAmelCase         =			0

						UpperCAmelCase         =			f"""Open Kight Tour cannot be performed on a board of size {n}"""
						raise ValueError(A  )


if __name__ == "__main__":
	import doctest

	doctest.testmod()









'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowercase    :    Any			     =  {
    """configuration_maskformer""": ["""MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MaskFormerConfig"""],
    """configuration_maskformer_swin""": ["""MaskFormerSwinConfig"""],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase    :    Any			     =  ["""MaskFormerFeatureExtractor"""]
	_lowercase    :    Dict			     =  ["""MaskFormerImageProcessor"""]


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase    :    Any			     =  [
	    """MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """MaskFormerForInstanceSegmentation""",
	    """MaskFormerModel""",
	    """MaskFormerPreTrainedModel""",
	]
	_lowercase    :    List[Any]			     =  [
	    """MaskFormerSwinBackbone""",
	    """MaskFormerSwinModel""",
	    """MaskFormerSwinPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
	from .configuration_maskformer_swin import MaskFormerSwinConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_maskformer import MaskFormerFeatureExtractor
		from .image_processing_maskformer import MaskFormerImageProcessor
	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_maskformer import (
		    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MaskFormerForInstanceSegmentation,
		    MaskFormerModel,
		    MaskFormerPreTrainedModel,
		)
		from .modeling_maskformer_swin import (
		    MaskFormerSwinBackbone,
		    MaskFormerSwinModel,
		    MaskFormerSwinPreTrainedModel,
		)


else:
	import sys

	_lowercase    :    List[Any]			     =  _LazyModule(__name__, globals()["""__file__"""], _import_structure)





