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 A__  (			lowercase:     Path,		lowercase:     list					)				->		Union[str, Any]:
							A						:     Optional[Any]         ='\n'.join(lowercase					)
							Path(lowercase					).open('w'					).writelines(lowercase					)


_lowercase							:      int      							='''patrickvonplaten/t5-tiny-random'''
_lowercase							:      List[str]      							='''sshleifer/bart-tiny-random'''
_lowercase							:      List[Any]      							='''sshleifer/tiny-mbart'''

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

									A						:     Dict         =str(Path(self.get_auto_remove_tmp_dir()     ) / 'scores.json'     )
									A						:     List[Any]         ='translation_en_to_de' if model == T5_TINY else 'summarization'
									A						:     Union[str, Any]         =f'\n            run_eval_search.py\n            {model}\n            {input_file_name}\n            {output_file_name}\n            --score_path {score_path}\n            --task {task}\n            --num_beams 2\n            --length_penalty 2.0\n            '.split()

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







		def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				str:
									self.run_eval_tester(SCREAMING_SNAKE_CASE__     )







		@parameterized.expand([BART_TINY, MBART_TINY]     )
		@slow
		def 		SCREAMING_SNAKE_CASE_		(				self    :					Any      ,	SCREAMING_SNAKE_CASE__    :					List[Any]     )    ->				List[Any]:
									self.run_eval_tester(SCREAMING_SNAKE_CASE__     )







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

									A						:     List[str]         ={
									    '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!',
									    ],
									}

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

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







import math



def A__  (			lowercase:     int					)				->		list:
       A						:     Optional[Any]         =[True] * n
       A						:     Tuple         =False
       A						:     List[Any]         =False
       A						:     Dict         =True

       for i in range(3,		int(n**0.5 + 1					),		2					):
              A						:     Dict         =i * 2
              while index < n:
                     A						:     Dict         =False
                     A						:     Dict         =index + i

       A						:     Tuple         =[2]

       for i in range(3,		lowercase,		2					):
              if is_prime[i]:
                     primes.append(lowercase					)

       return primes



def A__  (			lowercase:     int = 999_966_663_333					)				->		int:
       A						:     Optional[int]         =math.floor(math.sqrt(lowercase					)					) + 100
       A						:     Optional[int]         =prime_sieve(lowercase					)

       A						:     Optional[Any]         =0
       A						:     List[Any]         =0
       A						:     Union[str, Any]         =primes[prime_index]

       while (last_prime**2) <= limit:
              A						:     Tuple         =primes[prime_index + 1]

              A						:     Optional[int]         =last_prime**2
              A						:     Tuple         =next_prime**2

              # Get numbers divisible by lps(current)
              A						:     int         =lower_bound + last_prime
              while upper_bound > current <= limit:
                     matches_sum += current
                     current += last_prime

              # Reset the upper_bound
              while (upper_bound - next_prime) > limit:
                     upper_bound -= next_prime

              # Add the numbers divisible by ups(current)
              A						:     List[Any]         =upper_bound - next_prime
              while current > lower_bound:
                     matches_sum += current
                     current -= next_prime

              # Remove the numbers divisible by both ups and lps
              A						:     Any         =0
              while upper_bound > current <= limit:
                     if current <= lower_bound:
                            # Increment the current number
                            current += last_prime * next_prime
                            continue

                     if current > limit:
                            break

                     # Remove twice since it was added by both ups and lps
                     matches_sum -= current * 2

                     # Increment the current number
                     current += last_prime * next_prime

              # Setup for next pair
              A						:     List[str]         =next_prime
              prime_index += 1

       return matches_sum


if __name__ == "__main__":
    print(solution())






