


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







			__lowercase 					=   len(_UpperCamelCase  )
			__lowercase 					=   len(matrix[0]  )
			__lowercase 					=   min(_UpperCamelCase       ,			_UpperCamelCase  )

			for row in range(_UpperCamelCase  ):
						# Check if diagonal element is not zero
						if matrix[row][row] != 0:
									# Eliminate all the elements below the diagonal
									for col in range(row + 1       ,			_UpperCamelCase  ):
												__lowercase 					=   matrix[col][row] / matrix[row][row]
												for i in range(_UpperCamelCase       ,			_UpperCamelCase  ):
															matrix[col][i] -= multiplier * matrix[row][i]
						else:
									# Find a non-zero diagonal element to swap rows
									__lowercase 					=   True
									for i in range(row + 1       ,			_UpperCamelCase  ):
												if matrix[i][row] != 0:
															__lowercase					, __lowercase 					=   matrix[i], matrix[row]
															__lowercase 					=   False
															break
									if reduce:
												rank -= 1
												for i in range(_UpperCamelCase  ):
															__lowercase 					=   matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
									row -= 1

			return rank


if __name__ == "__main__":
	import doctest

	doctest.testmod()






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a : List[str]		=				{
    '''configuration_table_transformer''': [
        '''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TableTransformerConfig''',
        '''TableTransformerOnnxConfig''',
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a : Union[str, Any]		=				[
	    '''TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TableTransformerForObjectDetection''',
	    '''TableTransformerModel''',
	    '''TableTransformerPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_table_transformer import (
	    TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    TableTransformerConfig,
	    TableTransformerOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_table_transformer import (
		    TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TableTransformerForObjectDetection,
		    TableTransformerModel,
		    TableTransformerPreTrainedModel,
		)

else:
	import sys

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


