



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)
a__    =	logging.getLogger()



def       lowercase       (   SCREAMING_SNAKE_CASE__       :	Path				,       SCREAMING_SNAKE_CASE__       :	list				)  ->     List[str]:
 _snake_case    :  int					=					"""\n""".join(SCREAMING_SNAKE_CASE__				)
 Path(SCREAMING_SNAKE_CASE__				).open("""w"""				).writelines(SCREAMING_SNAKE_CASE__				)


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

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







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   def      UpperCamelCase_  (					self							:			List[Any]				,		lowerCAmelCase							:			Optional[Any])				->				Tuple:

    """simple docstring"""







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

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

    """simple docstring"""







    self.run_eval_tester(lowerCAmelCase)

   @parameterized.expand([BART_TINY, MBART_TINY])
   @slow
   def      UpperCamelCase_  (					self							:			int				,		lowerCAmelCase							:			Any)				->				Tuple:

    """simple docstring"""







    self.run_eval_tester(lowerCAmelCase)


   @parameterized.expand([T5_TINY, MBART_TINY])
   @slow
   def      UpperCamelCase_  (					self							:			str				,		lowerCAmelCase							:			int)				->				Any:

    """simple docstring"""







    _snake_case    :  List[Any]					=					Path(self.get_auto_remove_tmp_dir()) / """utest_input.source"""
    _snake_case    :  Any					=					input_file_name.parent / """utest_output.txt"""
    assert not output_file_name.exists()

    _snake_case    :  Optional[int]					=					{
        """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    :  Tuple					=					Path(self.get_auto_remove_tmp_dir())
    _snake_case    :  Union[str, Any]					=					str(tmp_dir / """scores.json""")
    _snake_case    :  int					=					str(tmp_dir / """val.target""")
    _dump_articles(lowerCAmelCase				,		text["""en"""])
    _dump_articles(lowerCAmelCase				,		text["""de"""])
    _snake_case    :  Any					=					"""translation_en_to_de""" if model == T5_TINY else """summarization"""
    _snake_case    :  Dict					=					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()
     _snake_case    :  Optional[int]					=					[""" num_beams | length_penalty""", model, """Best score args"""]
     _snake_case    :  Dict					=					["""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))





from math import ceil, sqrt



def       lowercase       (   SCREAMING_SNAKE_CASE__       :	int = 1_000_000				)  ->     int:
 _snake_case    :  Tuple					=					0

 for outer_width in range(3				,       (limit // 4) + 2				):
  if outer_width**2 > limit:
   _snake_case    :  int					=					max(ceil(sqrt(outer_width**2 - limit				)				)				,       1				)
  else:
   _snake_case    :  Any					=					1
  if (outer_width - hole_width_lower_bound) % 2:
   hole_width_lower_bound += 1

  answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

 return answer


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