
"""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							=				logging.getLogger()



def      lowerCAmelCase__			(		__magic_name__			,   __magic_name__      )						->Any:
			__lowercase       =       "\n".join(__magic_name__      )
			Path(__magic_name__      ).open("w"      ).writelines(__magic_name__      )


_lowercase							=				'''patrickvonplaten/t5-tiny-random'''
_lowercase							=				'''sshleifer/bart-tiny-random'''
_lowercase							=				'''sshleifer/tiny-mbart'''

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







class 					__a     ( __a       ):



							'''simple docstring'''







							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase       )			->							List[str]:




										'''simple docstring'''
										__lowercase       =       Path(self.get_auto_remove_tmp_dir()       ) / "utest_input.source"
										__lowercase       =       input_file_name.parent / "utest_output.txt"
										assert not output_file_name.exists()
										__lowercase       =       [" New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County."]
										_dump_articles(_lowerCamelCase  ,    _lowerCamelCase       )

										__lowercase       =       str(Path(self.get_auto_remove_tmp_dir()       ) / "scores.json"       )
										__lowercase       =       "translation_en_to_de" if model == T5_TINY else "summarization"
										__lowercase       =       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   SCREAMING_SNAKE_CASE						(     self       )			->							Tuple:




										'''simple docstring'''
										self.run_eval_tester(_lowerCamelCase       )
							@parameterized.expand([BART_TINY, MBART_TINY]       )
							@slow
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase       )			->							int:




										'''simple docstring'''
										self.run_eval_tester(_lowerCamelCase       )





							@parameterized.expand([T5_TINY, MBART_TINY]       )
							@slow
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase       )			->							Dict:




										'''simple docstring'''
										__lowercase       =       Path(self.get_auto_remove_tmp_dir()       ) / "utest_input.source"
										__lowercase       =       input_file_name.parent / "utest_output.txt"
										assert not output_file_name.exists()

										__lowercase       =       {
										    "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!",
										    ],
										}

										__lowercase       =       Path(self.get_auto_remove_tmp_dir()       )
										__lowercase       =       str(tmp_dir / "scores.json"       )
										__lowercase       =       str(tmp_dir / "val.target"       )
										_dump_articles(_lowerCamelCase  ,    text["en"]       )
										_dump_articles(_lowerCamelCase  ,    text["de"]       )
										__lowercase       =       "translation_en_to_de" if model == T5_TINY else "summarization"
										__lowercase       =       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()
													__lowercase       =       [" num_beams | length_penalty", model, "Best score args"]
													__lowercase       =       ["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      lowerCAmelCase__			(		__magic_name__ = 1_0      )						->str:
			if not isinstance(__magic_name__			,   __magic_name__      ) or n < 0:
						raise ValueError("Invalid input"      )
			__lowercase       =       1_0**n
			__lowercase       =       2_8_4_3_3 * (pow(2			,   7_8_3_0_4_5_7			,   __magic_name__      )) + 1
			return str(number % modulus      )


if __name__ == "__main__":
					from doctest import testmod

					testmod()
					print(F"{solution(10) = }")





