
from __future__ import annotations

import numpy as np



def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase	,						lowercase							=						np.shape(lowerCAmelCase__		)
					if rows != columns:
										lowercase							=						(
										    '''\'table\' has to be of square shaped array but got a '''
										    f'{rows}x{columns} array:\n{table}'
										)
										raise ValueError(lowerCAmelCase__		)

					lowercase							=						np.zeros((rows, columns)		)
					lowercase							=						np.zeros((rows, columns)		)
					for i in range(lowerCAmelCase__		):
										for j in range(lowerCAmelCase__		):
															lowercase							=						sum(lower[i][k] * upper[k][j] for k in range(lowerCAmelCase__		)		)
															if upper[j][j] == 0:
																				raise ArithmeticError('''No LU decomposition exists'''		)
															lowercase							=						(table[i][j] - total) / upper[j][j]
										lowercase							=						1
										for j in range(lowerCAmelCase__ ,			lowerCAmelCase__		):
															lowercase							=						sum(lower[i][k] * upper[k][j] for k in range(lowerCAmelCase__		)		)
															lowercase							=						table[i][j] - total
					return lower, upper


if __name__ == "__main__":
							import doctest

							doctest.testmod()











from typing import TYPE_CHECKING

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


UpperCAmelCase						:   Any			  =     {
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   int			  =     ['''MvpTokenizerFast''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   str			  =     [
				    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''MvpForCausalLM''',
				    '''MvpForConditionalGeneration''',
				    '''MvpForQuestionAnswering''',
				    '''MvpForSequenceClassification''',
				    '''MvpModel''',
				    '''MvpPreTrainedModel''',
				]

if TYPE_CHECKING:
				from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
				from .tokenization_mvp import MvpTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_mvp_fast import MvpTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mvp import (
								    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MvpForCausalLM,
								    MvpForConditionalGeneration,
								    MvpForQuestionAnswering,
								    MvpForSequenceClassification,
								    MvpModel,
								    MvpPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase						:   List[str]			  =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




