



'''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


lowercase_      :				str   					=    '''sshleifer/bart-tiny-random'''
lowercase_      :				List[str]   					=    '''patrickvonplaten/t5-tiny-random'''




@require_torch
class      __UpperCamelCase       (unittest.TestCase			):







	@cached_property
	def   _a   (    self						)    ->    int:
							'''simple docstring'''






							return AutoConfig.from_pretrained(_A						)







	def   _a   (    self						)    ->    List[Any]:
							'''simple docstring'''






							lowercase        =							create_student_by_copying_alternating_layers(_A ,				tempfile.mkdtemp() ,				e=1 ,				d=1						)
							self.assertEqual(student.config.num_hidden_layers ,				1						)







	def   _a   (    self						)    ->    Union[str, Any]:
							'''simple docstring'''






							lowercase        =							create_student_by_copying_alternating_layers(_A ,				tempfile.mkdtemp() ,				e=1 ,				d=_A						)







	def   _a   (    self						)    ->    Union[str, Any]:
							'''simple docstring'''






							lowercase        =							create_student_by_copying_alternating_layers(_A ,				tempfile.mkdtemp() ,				e=1 ,				d=_A						)
							self.assertEqual(student.config.encoder_layers ,				1						)
							self.assertEqual(student.config.decoder_layers ,				self.teacher_config.encoder_layers						)







	def   _a   (    self						)    ->    Dict:
							'''simple docstring'''






							lowercase        =							create_student_by_copying_alternating_layers(_A ,				tempfile.mkdtemp() ,				e=1 ,				d=1						)
							self.assertEqual(student.config.encoder_layers ,				1						)
							self.assertEqual(student.config.decoder_layers ,				1						)







	def   _a   (    self						)    ->    Any:
							'''simple docstring'''






							with self.assertRaises(_A						):
													create_student_by_copying_alternating_layers(_A ,				tempfile.mkdtemp() ,				e=_A ,				d=_A						)








'''simple docstring'''


def      SCREAMING_SNAKE_CASE				(				lowercase_    :      int ,  lowercase_    :      int ,  lowercase_    :      list[list[int]]						):

						def update_area_of_max_square(lowercase_    :      int ,  lowercase_    :      int						) -> int:
												# BASE CASE
												if row >= rows or col >= cols:
																		return 0

												lowercase        =							update_area_of_max_square(lowercase_ ,  col + 1						)
												lowercase        =							update_area_of_max_square(row + 1 ,  col + 1						)
												lowercase        =							update_area_of_max_square(row + 1 ,  lowercase_						)

												if mat[row][col]:
																		lowercase        =							1 + min([right, diagonal, down]						)
																		lowercase        =							max(largest_square_area[0] ,  lowercase_						)
																		return sub_problem_sol
												else:
																		return 0

						lowercase        =							[0]
						update_area_of_max_square(0 ,  0						)
						return largest_square_area[0]







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      int ,  lowercase_    :      int ,  lowercase_    :      list[list[int]]						):

						def update_area_of_max_square_using_dp_array(
						    lowercase_    :      int ,  lowercase_    :      int ,  lowercase_    :      list[list[int]]						) -> int:
												if row >= rows or col >= cols:
																		return 0
												if dp_array[row][col] != -1:
																		return dp_array[row][col]

												lowercase        =							update_area_of_max_square_using_dp_array(lowercase_ ,  col + 1 ,  lowercase_						)
												lowercase        =							update_area_of_max_square_using_dp_array(row + 1 ,  col + 1 ,  lowercase_						)
												lowercase        =							update_area_of_max_square_using_dp_array(row + 1 ,  lowercase_ ,  lowercase_						)

												if mat[row][col]:
																		lowercase        =							1 + min([right, diagonal, down]						)
																		lowercase        =							max(largest_square_area[0] ,  lowercase_						)
																		lowercase        =							sub_problem_sol
																		return sub_problem_sol
												else:
																		return 0

						lowercase        =							[0]
						lowercase        =							[[-1] * cols for _ in range(lowercase_						)]
						update_area_of_max_square_using_dp_array(0 ,  0 ,  lowercase_						)

						return largest_square_area[0]







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      int ,  lowercase_    :      int ,  lowercase_    :      list[list[int]]						):
						lowercase        =							[[0] * (cols + 1) for _ in range(rows + 1						)]
						lowercase        =							0
						for row in range(rows - 1 ,  -1 ,  -1						):
												for col in range(cols - 1 ,  -1 ,  -1						):
																		lowercase        =							dp_array[row][col + 1]
																		lowercase        =							dp_array[row + 1][col + 1]
																		lowercase        =							dp_array[row + 1][col]

																		if mat[row][col] == 1:
																								lowercase        =							1 + min(lowercase_ ,  lowercase_ ,  lowercase_						)
																								lowercase        =							max(dp_array[row][col] ,  lowercase_						)
																		else:
																								lowercase        =							0

						return largest_square_area







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      int ,  lowercase_    :      int ,  lowercase_    :      list[list[int]]						):
						lowercase        =							[0] * (cols + 1)
						lowercase        =							[0] * (cols + 1)
						lowercase        =							0
						for row in range(rows - 1 ,  -1 ,  -1						):
												for col in range(cols - 1 ,  -1 ,  -1						):
																		lowercase        =							current_row[col + 1]
																		lowercase        =							next_row[col + 1]
																		lowercase        =							next_row[col]

																		if mat[row][col] == 1:
																								lowercase        =							1 + min(lowercase_ ,  lowercase_ ,  lowercase_						)
																								lowercase        =							max(current_row[col] ,  lowercase_						)
																		else:
																								lowercase        =							0
												lowercase        =							current_row

						return largest_square_area


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))


