



"""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)
lowerCamelCase       	=						logging.getLogger()
def        a__     (				lowerCAmelCase__     ,      lowerCAmelCase__				):
      UpperCAmelCase_      			=							"\n".join(lowerCAmelCase__				)
      Path(lowerCAmelCase__				).open("w"				).writelines(lowerCAmelCase__				)


lowerCamelCase       	=						"""patrickvonplaten/t5-tiny-random"""
lowerCamelCase       	=						"""sshleifer/bart-tiny-random"""
lowerCamelCase       	=						"""sshleifer/tiny-mbart"""

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


class 				lowercase__       (   SCREAMING_SNAKE_CASE				):







       '''simple docstring'''


       def 					lowercase__    (							self      :  str		,    _UpperCAmelCase      :  List[str]   )			->						List[Any]:


             '''simple docstring'''




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

             UpperCAmelCase_      			=							str(Path(self.get_auto_remove_tmp_dir()   ) / "scores.json"   )
             UpperCAmelCase_      			=							"translation_en_to_de" if model == T5_TINY else "summarization"
             UpperCAmelCase_      			=							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 					lowercase__    (							self      :  Optional[Any]   )			->						int:


             '''simple docstring'''




             self.run_eval_tester(_UpperCAmelCase   )



       @parameterized.expand([BART_TINY, MBART_TINY]   )
       @slow
       def 					lowercase__    (							self      :  Optional[int]		,    _UpperCAmelCase      :  Optional[Any]   )			->						Optional[int]:


             '''simple docstring'''




             self.run_eval_tester(_UpperCAmelCase   )







       @parameterized.expand([T5_TINY, MBART_TINY]   )
       @slow
       def 					lowercase__    (							self      :  Optional[int]		,    _UpperCAmelCase      :  str   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							Path(self.get_auto_remove_tmp_dir()   ) / "utest_input.source"
             UpperCAmelCase_      			=							input_file_name.parent / "utest_output.txt"
             assert not output_file_name.exists()

             UpperCAmelCase_      			=							{
                 "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!",
                 ],
             }

             UpperCAmelCase_      			=							Path(self.get_auto_remove_tmp_dir()   )
             UpperCAmelCase_      			=							str(tmp_dir / "scores.json"   )
             UpperCAmelCase_      			=							str(tmp_dir / "val.target"   )
             _dump_articles(_UpperCAmelCase		,    text["en"]   )
             _dump_articles(_UpperCAmelCase		,    text["de"]   )
             UpperCAmelCase_      			=							"translation_en_to_de" if model == T5_TINY else "summarization"
             UpperCAmelCase_      			=							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()
                   UpperCAmelCase_      			=							[" num_beams | length_penalty", model, "Best score args"]
                   UpperCAmelCase_      			=							["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   )   )









"""simple docstring"""





def        a__     (				lowerCAmelCase__ = 2000000				):
      UpperCAmelCase_      			=							[0 for i in range(n + 1				)]
      UpperCAmelCase_      			=							1
      UpperCAmelCase_      			=							1

      for i in range(2     ,      int(n**0.5				) + 1				):
            if primality_list[i] == 0:
                  for j in range(i * i     ,      n + 1     ,      lowerCAmelCase__				):
                        UpperCAmelCase_      			=							1
      UpperCAmelCase_      			=							0
      for i in range(lowerCAmelCase__				):
            if primality_list[i] == 0:
                  sum_of_primes += i
      return sum_of_primes


if __name__ == "__main__":
  print(F"{solution() = }")




