






def    UpperCamelCase__  (   UpperCAmelCase     )     ->		bool:







							"""simple docstring"""





							_a  :    Any			=						[list(UpperCAmelCase     ) for row in matrix]
							if matrix and isinstance(UpperCAmelCase    ,	UpperCAmelCase     ):
														if isinstance(matrix[0]    ,	UpperCAmelCase     ):
																					_a  :    Tuple			=						0
																					for row in matrix:
																												if prev_len == 0:
																																			_a  :    Dict			=						len(UpperCAmelCase     )
																																			_a  :    int			=						True
																												else:
																																			_a  :    Tuple			=						prev_len == len(UpperCAmelCase     )
														else:
																					_a  :    List[str]			=						True
							else:
														_a  :    List[str]			=						False

							return result






def    UpperCamelCase__  (   UpperCAmelCase     )     ->		None:







							"""simple docstring"""





							if check_matrix(UpperCAmelCase     ) and len(UpperCAmelCase     ) > 0:
														_a  :    Optional[Any]			=						[list(UpperCAmelCase     ) for row in a]
														_a  :    str			=						len(UpperCAmelCase     )
														if isinstance(a[0]    ,	UpperCAmelCase     ):
																					_a  :    Union[str, Any]			=						len(a[0]     )
														else:
																					for dat in a:
																												print(UpperCAmelCase     )
																					return

														# horizotal printing increasing
														for i in range(0    ,	UpperCAmelCase     ):
																					print(a[0][i]     )
														# vertical printing down
														for i in range(1    ,	UpperCAmelCase     ):
																					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]     )
														_a  :    str			=						[row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
														if len(UpperCAmelCase     ) > 0:
																					spiral_print_clockwise(UpperCAmelCase     )
														else:
																					return
							else:
														print('''Not a valid matrix'''     )
														return






def    UpperCamelCase__  (   UpperCAmelCase     )     ->		list[int]:







							"""simple docstring"""





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


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

						doctest.testmod()

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







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCamelCase						= {
    'configuration_bart': ['BART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BartConfig', 'BartOnnxConfig'],
    'tokenization_bart': ['BartTokenizer'],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= ['BartTokenizerFast']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'BART_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'BartForCausalLM',
						    'BartForConditionalGeneration',
						    'BartForQuestionAnswering',
						    'BartForSequenceClassification',
						    'BartModel',
						    'BartPretrainedModel',
						    'PretrainedBartModel',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'TFBartForConditionalGeneration',
						    'TFBartForSequenceClassification',
						    'TFBartModel',
						    'TFBartPretrainedModel',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'FlaxBartDecoderPreTrainedModel',
						    'FlaxBartForCausalLM',
						    'FlaxBartForConditionalGeneration',
						    'FlaxBartForQuestionAnswering',
						    'FlaxBartForSequenceClassification',
						    'FlaxBartModel',
						    'FlaxBartPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
						from .tokenization_bart import BartTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_bart_fast import BartTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_bart import (
												    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BartForCausalLM,
												    BartForConditionalGeneration,
												    BartForQuestionAnswering,
												    BartForSequenceClassification,
												    BartModel,
												    BartPretrainedModel,
												    PretrainedBartModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_bart import (
												    TFBartForConditionalGeneration,
												    TFBartForSequenceClassification,
												    TFBartModel,
												    TFBartPretrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_bart import (
												    FlaxBartDecoderPreTrainedModel,
												    FlaxBartForCausalLM,
												    FlaxBartForConditionalGeneration,
												    FlaxBartForQuestionAnswering,
												    FlaxBartForSequenceClassification,
												    FlaxBartModel,
												    FlaxBartPreTrainedModel,
												)

else:
						import sys

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