






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)

UpperCamelCase								=		logging.getLogger()






def    __magic_name__    (	)     ->    Any:
							_lowercase							:   str 							=   argparse.ArgumentParser()
							parser.add_argument('-f'				)
							_lowercase							:   int 							=   parser.parse_args()
							return args.f






class 				lowerCAmelCase_	(		SCREAMING_SNAKE_CASE__			):


				def 						__a					(					self      ):
											_lowercase							:   Tuple 							=   logging.StreamHandler(sys.stdout      )
											logger.addHandler(snake_case__      )


				def 						__a					(					self ,						_lowerCAmelCase      ):
											_lowercase							:   Optional[Any] 							=   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(snake_case__ ,						'argv' ,						snake_case__      ):
																									_lowercase							:   List[Any] 							=   run_glue_deebert.main()
																									for value in result.values():
																																self.assertGreaterEqual(snake_case__ ,						0.6_66      )


				@slow
				@require_torch_non_multi_gpu
				def 						__a					(					self      ):
											_lowercase							:   str 							=   '\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            '.split()
											self.run_and_check(snake_case__      )

											_lowercase							:   Optional[Any] 							=   '\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --eval_each_highway\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
											self.run_and_check(snake_case__      )

											_lowercase							:   Any 							=   '\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --early_exit_entropy 0.1\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
											self.run_and_check(snake_case__      )










def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase )->	List[str]:
		SCREAMING_SNAKE_CASE_					      =							[1]
		for i in range(2    ,						lowerCAmelCase ):
				factorials.append(factorials[-1] * i )
		assert 0 <= k < factorials[-1] * n, "k out of bounds"

		SCREAMING_SNAKE_CASE_					      =							[]
		SCREAMING_SNAKE_CASE_					      =							list(range(lowerCAmelCase ) )

		# Find permutation
		while factorials:
				SCREAMING_SNAKE_CASE_					      =							factorials.pop()
				SCREAMING_SNAKE_CASE_      ,				SCREAMING_SNAKE_CASE_					      =							divmod(lowerCAmelCase    ,						lowerCAmelCase )
				permutation.append(elements[number] )
				elements.remove(elements[number] )
		permutation.append(elements[0] )

		return permutation


if __name__ == "__main__":
						import doctest

						doctest.testmod()