

from typing import TYPE_CHECKING

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


lowerCAmelCase_       	=	{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	['''BeitFeatureExtractor''']
					lowerCAmelCase_       	=	['''BeitImageProcessor''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''BeitForImageClassification''',
					    '''BeitForMaskedImageModeling''',
					    '''BeitForSemanticSegmentation''',
					    '''BeitModel''',
					    '''BeitPreTrainedModel''',
					]


try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''FlaxBeitForImageClassification''',
					    '''FlaxBeitForMaskedImageModeling''',
					    '''FlaxBeitModel''',
					    '''FlaxBeitPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_beit import BeitFeatureExtractor
										from .image_processing_beit import BeitImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_beit import (
										    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BeitForImageClassification,
										    BeitForMaskedImageModeling,
										    BeitForSemanticSegmentation,
										    BeitModel,
										    BeitPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_beit import (
										    FlaxBeitForImageClassification,
										    FlaxBeitForMaskedImageModeling,
										    FlaxBeitModel,
										    FlaxBeitPreTrainedModel,
										)


else:
					import sys

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


from __future__ import annotations


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	len(SCREAMING_SNAKE_CASE__       )
						# We need to create solution object to save path.
						snake_case_   =	[[0 for _ in range(SCREAMING_SNAKE_CASE__       )] for _ in range(SCREAMING_SNAKE_CASE__       )]
						snake_case_   =	run_maze(SCREAMING_SNAKE_CASE__  ,		0  ,		0  ,		SCREAMING_SNAKE_CASE__       )
						if solved:
												print('''\n'''.join(str(SCREAMING_SNAKE_CASE__       ) for row in solutions       )       )
						else:
												print('''No solution exists!'''       )
						return solved


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	len(SCREAMING_SNAKE_CASE__       )
						# Final check point.
						if i == j == (size - 1):
												snake_case_   =	1
												return True

						snake_case_   =	(not i < 0) and (not j < 0)  # Check lower bounds
						snake_case_   =	(i < size) and (j < size)  # Check upper bounds

						if lower_flag and upper_flag:
												# check for already visited and block points.
												snake_case_   =	(not solutions[i][j]) and (not maze[i][j])
												if block_flag:
																		# check visited
																		snake_case_   =	1

																		# check for directions
																		if (
																		    run_maze(SCREAMING_SNAKE_CASE__  ,		i + 1  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )
																		    or run_maze(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		j + 1  ,		SCREAMING_SNAKE_CASE__       )
																		    or run_maze(SCREAMING_SNAKE_CASE__  ,		i - 1  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )
																		    or run_maze(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		j - 1  ,		SCREAMING_SNAKE_CASE__       )
																		):
																								return True

																		snake_case_   =	0
																		return False
						return False


if __name__ == "__main__":
					import doctest

					doctest.testmod()