





def 				SCREAMING_SNAKE_CASE__    (     __a ):
	# must be
	snake_case_		:      str           =						[list(__a ) for row in matrix]
	if matrix and isinstance(__a ,			__a ):
		if isinstance(matrix[0] ,			__a ):
			snake_case_		:      Union[str, Any]           =						0
			for row in matrix:
				if prev_len == 0:
					snake_case_		:      str           =						len(__a )
					snake_case_		:      Union[str, Any]           =						True
				else:
					snake_case_		:      List[str]           =						prev_len == len(__a )
		else:
			snake_case_		:      List[Any]           =						True
	else:
		snake_case_		:      Optional[Any]           =						False

	return result


def 				SCREAMING_SNAKE_CASE__    (     __a ):
	if check_matrix(__a ) and len(__a ) > 0:
		snake_case_		:      Tuple           =						[list(__a ) for row in a]
		snake_case_		:      Dict           =						len(__a )
		if isinstance(a[0] ,			__a ):
			snake_case_		:      Any           =						len(a[0] )
		else:
			for dat in a:
				print(__a )
			return

		# horizotal printing increasing
		for i in range(0 ,			__a ):
			print(a[0][i] )
		# vertical printing down
		for i in range(1 ,			__a ):
			print(a[i][mat_col - 1] )
		# horizotal printing decreasing
		if mat_row > 1:
			for i in range(mat_col - 2 ,			-1 ,			-1 ):
				print(a[mat_row - 1][i] )
        # vertical printing up
		for i in range(mat_row - 2 ,			0 ,			-1 ):
			print(a[i][0] )
		snake_case_		:      int           =						[row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
		if len(__a ) > 0:
			spiral_print_clockwise(__a )
		else:
			return
	else:
		print('Not a valid matrix' )
		return


def 				SCREAMING_SNAKE_CASE__    (     __a ):
	if matrix:
		return list(matrix.pop(0 ) ) + spiral_traversal(list(zip(*__a ) )[::-1] )
	else:
		return []


# driver code
if __name__ == "__main__":
						import doctest

						doctest.testmod()

						_SCREAMING_SNAKE_CASE   						=		[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
						spiral_print_clockwise(a)









'''simple docstring'''


from typing import TYPE_CHECKING

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


lowerCamelCase_					:			Any     						=				{
    '''configuration_sam''': [
        '''SAM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SamConfig''',
        '''SamMaskDecoderConfig''',
        '''SamPromptEncoderConfig''',
        '''SamVisionConfig''',
    ],
    '''processing_sam''': ['''SamProcessor'''],
}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase_					:			Union[str, Any]     						=				[
					    '''SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''SamModel''',
					    '''SamPreTrainedModel''',
					]
try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase_					:			Optional[Any]     						=				[
					    '''TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFSamModel''',
					    '''TFSamPreTrainedModel''',
					]
try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase_					:			Optional[Any]     						=				['''SamImageProcessor''']


if TYPE_CHECKING:
					from .configuration_sam import (
					    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SamConfig,
					    SamMaskDecoderConfig,
					    SamPromptEncoderConfig,
					    SamVisionConfig,
					)
					from .processing_sam import SamProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_sam import SamImageProcessor

else:
					import sys

					lowerCamelCase_					:			Optional[Any]     						=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
