
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_      (       A__			,		A__		)							->							Optional[Any]:
    """simple docstring"""

    snake_case								= "\n".join(A__		)
    Path(A__		).open("w"		).writelines(A__		)


_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 					lowerCamelCase		(  A_  ):





     def 		UpperCAmelCase(self				:   Optional[Any]    ,   _A				:   Union[str, Any]       )						->						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(_A    ,   _A       )

         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'\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(_A    ,   "argv"    ,   _A       ):
             run_generate()
             assert Path(_A       ).exists()
             # os.remove(Path(output_file_name))





     def 		UpperCAmelCase(self				:   Dict       )						->						int:
         self.run_eval_tester(_A       )





     @parameterized.expand([BART_TINY, MBART_TINY]       )
     @slow
     def 		UpperCAmelCase(self				:   str    ,   _A				:   str       )						->						Tuple:
         self.run_eval_tester(_A       )





     @parameterized.expand([T5_TINY, MBART_TINY]       )
     @slow
     def 		UpperCAmelCase(self				:   Union[str, Any]    ,   _A				:   Optional[Any]       )						->						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(_A    ,   text["en"]       )
         _dump_articles(_A    ,   text["de"]       )
         snake_case								= "translation_en_to_de" if model == T5_TINY else "summarization"
         snake_case								= f'\n            run_eval_search.py\n            {model}\n            {str(_A       )}\n            {str(_A       )}\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(_A    ,   "argv"    ,   _A       ):
             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(_A       )
             for w in expected_strings:
                 assert w in cs.out
             for w in un_expected_strings:
                 assert w not in cs.out
             assert Path(_A       ).exists()
             os.remove(Path(_A       )       )



from ....utils import logging


_A   =			logging.get_logger(__name__)







class 					lowerCamelCase		(  A_  ):





     def __init__(self				:   Tuple    ,   _A				:   Optional[int]    ,   _A				:   Tuple=None    ,   _A				:   Union[str, Any]=2_0_4_8       )						->						List[Any]:
         snake_case								= config.__dict__
         snake_case								= modal_hidden_size
         if num_labels:
             snake_case								= num_labels

