



"""simple docstring"""
from __future__ import annotations

import numpy as np



def        lowerCAmelCase_(   lowercase_     :							Any							)	->       tuple[np.ndarray, np.ndarray]:
				_lowerCamelCase  ,     _lowerCamelCase        =				np.shape(UpperCamelCase__							)
				if rows != columns:
								_lowerCamelCase        =				(
								    '''\'table\' has to be of square shaped array but got a '''
								    F"""{rows}x{columns} array:\n{table}"""
								)
								raise ValueError(UpperCamelCase__							)

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


if __name__ == "__main__":
			import doctest

			doctest.testmod()





"""simple docstring"""
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
			if not (is_transformers_available() and is_torch_available()):
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
			from .pipeline_kandinsky import KandinskyPipeline
			from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
			from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
			from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
			from .text_encoder import MultilingualCLIP
