






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)
__UpperCamelCase					:		List[Any]	  =						logging.getLogger()
def      a_ (      _A      ,   _A  )			->			Dict:







				"""simple docstring"""
				snake_case__									=     '\n'.join(_A  )
				Path(_A  ).open('w'  ).writelines(_A  )


__UpperCamelCase					:		int	  =						"""patrickvonplaten/t5-tiny-random"""
__UpperCamelCase					:		Dict	  =						"""sshleifer/bart-tiny-random"""
__UpperCamelCase					:		Optional[Any]	  =						"""sshleifer/tiny-mbart"""

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


class   __SCREAMING_SNAKE_CASE(	a_	):
							def lowerCAmelCase_ (     self:      List[str]       ,	UpperCamelCase:      Tuple						)		->		List[str]:
											snake_case__									=     Path(self.get_auto_remove_tmp_dir()						) / 'utest_input.source'
											snake_case__									=     input_file_name.parent / 'utest_output.txt'
											assert not output_file_name.exists()
											snake_case__									=     [' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
											_dump_articles(UpperCamelCase       ,	UpperCamelCase						)

											snake_case__									=     str(Path(self.get_auto_remove_tmp_dir()						) / 'scores.json'						)
											snake_case__									=     'translation_en_to_de' if model == T5_TINY else 'summarization'
											snake_case__									=     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(UpperCamelCase       ,	'argv'       ,	UpperCamelCase						):
															run_generate()
															assert Path(UpperCamelCase						).exists()
															# os.remove(Path(output_file_name))
							def lowerCAmelCase_ (     self:      Optional[Any]						)		->		List[str]:
											self.run_eval_tester(UpperCamelCase						)
							@parameterized.expand([BART_TINY, MBART_TINY]						)
							@slow
							def lowerCAmelCase_ (     self:      int       ,	UpperCamelCase:      str						)		->		Dict:
											self.run_eval_tester(UpperCamelCase						)


							@parameterized.expand([T5_TINY, MBART_TINY]						)
							@slow
							def lowerCAmelCase_ (     self:      int       ,	UpperCamelCase:      Dict						)		->		str:
											snake_case__									=     Path(self.get_auto_remove_tmp_dir()						) / 'utest_input.source'
											snake_case__									=     input_file_name.parent / 'utest_output.txt'
											assert not output_file_name.exists()

											snake_case__									=     {
											    '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!',
											    ],
											}

											snake_case__									=     Path(self.get_auto_remove_tmp_dir()						)
											snake_case__									=     str(tmp_dir / 'scores.json'						)
											snake_case__									=     str(tmp_dir / 'val.target'						)
											_dump_articles(UpperCamelCase       ,	text['en']						)
											_dump_articles(UpperCamelCase       ,	text['de']						)
											snake_case__									=     'translation_en_to_de' if model == T5_TINY else 'summarization'
											snake_case__									=     F'''
            run_eval_search.py
            {model}
            {str(UpperCamelCase						)}
            {str(UpperCamelCase						)}
            --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(UpperCamelCase       ,	'argv'       ,	UpperCamelCase						):
															with CaptureStdout() as cs:
																			run_search()
															snake_case__									=     [' num_beams | length_penalty', model, 'Best score args']
															snake_case__									=     ['Info']
															if "translation" in task:
																			expected_strings.append('bleu'						)
															else:
																			expected_strings.extend(UpperCamelCase						)
															for w in expected_strings:
																			assert w in cs.out
															for w in un_expected_strings:
																			assert w not in cs.out
															assert Path(UpperCamelCase						).exists()
															os.remove(Path(UpperCamelCase						)						)












from __future__ import annotations
def      a_ (      _A  )			->			bool:







				"""simple docstring"""
				return len(set(_A  )  ) == len(_A  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()




