



"""simple docstring"""






import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
_lowercase				:				Any   		=		logging.getLogger()






def   snake_case__     (	__lowerCamelCase       :					Path							,	__lowerCamelCase       :					list			):
			"""simple docstring"""
			lowerCamelCase__	:	List[str]				='''\n'''.join(__lowerCamelCase			)
			Path(__lowerCamelCase			).open('''w'''			).writelines(__lowerCamelCase			)


_lowercase				:				List[Any]   		=		"patrickvonplaten/t5-tiny-random"
_lowercase				:				Optional[Any]   		=		"sshleifer/bart-tiny-random"
_lowercase				:				Tuple   		=		"sshleifer/tiny-mbart"

_lowercase				:				List[Any]   		=		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks

class  __SCREAMING_SNAKE_CASE			(   lowerCAmelCase_     ):


					'''simple docstring'''





					def 	snake_case ( self							:						str,						lowerCamelCase							:						Union[str, Any]  )->      List[str]:
								lowerCamelCase__	:	Dict				=Path(self.get_auto_remove_tmp_dir()  ) / '''utest_input.source'''
								lowerCamelCase__	:	int				=input_file_name.parent / '''utest_output.txt'''
								assert not output_file_name.exists()
								lowerCamelCase__	:	int				=[''' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.''']
								_dump_articles(lowerCamelCase,						lowerCamelCase  )

								lowerCamelCase__	:	int				=str(Path(self.get_auto_remove_tmp_dir()  ) / '''scores.json'''  )
								lowerCamelCase__	:	int				='''translation_en_to_de''' if model == T5_TINY else '''summarization'''
								lowerCamelCase__	:	Optional[int]				=F'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase  ):
											run_generate()
											assert Path(lowerCamelCase  ).exists()
											# os.remove(Path(output_file_name))



					def 	snake_case ( self							:						Dict  )->      Dict:
								self.run_eval_tester(lowerCamelCase  )



					@parameterized.expand([BART_TINY, MBART_TINY]  )
					@slow
					def 	snake_case ( self							:						List[str],						lowerCamelCase							:						Tuple  )->      Tuple:
								self.run_eval_tester(lowerCamelCase  )




					@parameterized.expand([T5_TINY, MBART_TINY]  )
					@slow
					def 	snake_case ( self							:						Union[str, Any],						lowerCamelCase							:						Any  )->      Optional[int]:
								lowerCamelCase__	:	int				=Path(self.get_auto_remove_tmp_dir()  ) / '''utest_input.source'''
								lowerCamelCase__	:	Any				=input_file_name.parent / '''utest_output.txt'''
								assert not output_file_name.exists()

								lowerCamelCase__	:	Any				={
								    '''en''': ['''Machine learning is great, isn\'t it?''', '''I like to eat bananas''', '''Tomorrow is another great day!'''],
								    '''de''': [
								        '''Maschinelles Lernen ist großartig, oder?''',
								        '''Ich esse gerne Bananen''',
								        '''Morgen ist wieder ein toller Tag!''',
								    ],
								}

								lowerCamelCase__	:	Optional[int]				=Path(self.get_auto_remove_tmp_dir()  )
								lowerCamelCase__	:	List[str]				=str(tmp_dir / '''scores.json'''  )
								lowerCamelCase__	:	str				=str(tmp_dir / '''val.target'''  )
								_dump_articles(lowerCamelCase,						text['''en''']  )
								_dump_articles(lowerCamelCase,						text['''de''']  )
								lowerCamelCase__	:	int				='''translation_en_to_de''' if model == T5_TINY else '''summarization'''
								lowerCamelCase__	:	str				=F'''
            run_eval_search.py
            {model}
            {str(lowerCamelCase  )}
            {str(lowerCamelCase  )}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
								testargs.extend(['''--search''', '''num_beams=1:2 length_penalty=0.9:1.0''']  )

								with patch.object(lowerCamelCase,						'''argv''',						lowerCamelCase  ):
											with CaptureStdout() as cs:
														run_search()
											lowerCamelCase__	:	Dict				=[''' num_beams | length_penalty''', model, '''Best score args''']
											lowerCamelCase__	:	Optional[Any]				=['''Info''']
											if "translation" in task:
														expected_strings.append('''bleu'''  )
											else:
														expected_strings.extend(lowerCamelCase  )
											for w in expected_strings:
														assert w in cs.out
											for w in un_expected_strings:
														assert w not in cs.out
											assert Path(lowerCamelCase  ).exists()
											os.remove(Path(lowerCamelCase  )  )









"""simple docstring"""






def   snake_case__     (	__lowerCamelCase       :					str			):
			"""simple docstring"""
			return " ".join(
			    ''''''.join(word[::-1]			) if len(__lowerCamelCase			) > 4 else word for word in sentence.split()			)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(reverse_long_words("Hey wollef sroirraw"))




