



'''simple docstring'''


import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

lowercase_      :				int   					=    logging.getLogger()







def      SCREAMING_SNAKE_CASE				(				):
						lowercase        =							argparse.ArgumentParser()
						parser.add_argument("""-f"""						)
						lowercase        =							parser.parse_args()
						return args.f




class      __UpperCamelCase       (_UpperCAmelCase			):







	def   _a   (    self						)    ->    None:
							'''simple docstring'''






							lowercase        =							logging.StreamHandler(sys.stdout						)
							logger.addHandler(_lowerCAmelCase						)







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






							lowercase        =							get_gpu_count()

							if n_gpu > 1:
													pass
													# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
													# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
													# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
													# cmd = [sys.executable] + distributed_args + args
													# execute_subprocess_async(cmd, env=self.get_env())
													# XXX: test the results - need to save them first into .json file
							else:
													args.insert(0 ,				"""run_glue_deebert.py"""						)
													with patch.object(_lowerCAmelCase ,				"""argv""" ,				_lowerCAmelCase						):
																			lowercase        =							run_glue_deebert.main()
																			for value in result.values():
																									self.assertGreaterEqual(_lowerCAmelCase ,				0.666						)







	@slow
	@require_torch_non_multi_gpu
	def   _a   (    self						)    ->    Tuple:
							'''simple docstring'''






							lowercase        =							"""
            --model_type roberta
            --model_name_or_path roberta-base
            --task_name MRPC
            --do_train
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --max_seq_length 128
            --per_gpu_eval_batch_size=1
            --per_gpu_train_batch_size=8
            --learning_rate 2e-4
            --num_train_epochs 3
            --overwrite_output_dir
            --seed 42
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --save_steps 0
            --overwrite_cache
            --eval_after_first_stage
            """.split()
							self.run_and_check(_lowerCAmelCase						)

							lowercase        =							"""
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --eval_each_highway
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
							self.run_and_check(_lowerCAmelCase						)

							lowercase        =							"""
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --early_exit_entropy 0.1
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
							self.run_and_check(_lowerCAmelCase						)







'''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]]))


