



'''simple docstring'''
import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


snake_case_			:     Optional[int]  	=  'sshleifer/bart-tiny-random'
snake_case_			:     Tuple  	=  'patrickvonplaten/t5-tiny-random'






@require_torch
class 							lowercase__     (							unittest.TestCase       ):





	@cached_property
	def      UpperCamelCase_  (			self :    Optional[int]			):







							'''simple docstring'''
							return AutoConfig.from_pretrained(lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    Any			):







							'''simple docstring'''
							_UpperCamelCase :		int			    =       create_student_by_copying_alternating_layers(lowerCamelCase__			,tempfile.mkdtemp()			,e=1			,d=1			)
							self.assertEqual(student.config.num_hidden_layers			,1			)





	def      UpperCamelCase_  (			self :    List[Any]			):







							'''simple docstring'''
							_UpperCamelCase :		int			    =       create_student_by_copying_alternating_layers(lowerCamelCase__			,tempfile.mkdtemp()			,e=1			,d=lowerCamelCase__			)





	def      UpperCamelCase_  (			self :    Dict			):







							'''simple docstring'''
							_UpperCamelCase :		int			    =       create_student_by_copying_alternating_layers(lowerCamelCase__			,tempfile.mkdtemp()			,e=1			,d=lowerCamelCase__			)
							self.assertEqual(student.config.encoder_layers			,1			)
							self.assertEqual(student.config.decoder_layers			,self.teacher_config.encoder_layers			)





	def      UpperCamelCase_  (			self :    Any			):







							'''simple docstring'''
							_UpperCamelCase :		Any			    =       create_student_by_copying_alternating_layers(lowerCamelCase__			,tempfile.mkdtemp()			,e=1			,d=1			)
							self.assertEqual(student.config.encoder_layers			,1			)
							self.assertEqual(student.config.decoder_layers			,1			)





	def      UpperCamelCase_  (			self :    List[Any]			):







							'''simple docstring'''
							with self.assertRaises(lowerCamelCase__			):
													create_student_by_copying_alternating_layers(lowerCamelCase__			,tempfile.mkdtemp()			,e=lowerCamelCase__			,d=lowerCamelCase__			)










'''simple docstring'''
from __future__ import annotations

import numpy as np






def A__   (					UpperCAmelCase_							):
						_UpperCamelCase    ,      _UpperCamelCase :		Optional[int]			    =       np.shape(UpperCAmelCase_							)
						if rows != columns:
												_UpperCamelCase :		Union[str, Any]			    =       (
												    '\'table\' has to be of square shaped array but got a '
												    f'{rows}x{columns} array:\n{table}'
												)
												raise ValueError(UpperCAmelCase_							)

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


if __name__ == "__main__":
					import doctest

					doctest.testmod()


