





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)
SCREAMING_SNAKE_CASE_		     = logging.getLogger()



def      __lowercase     (   _SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)				->     str:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE	=		"""\n""".join(_SCREAMING_SNAKE_CASE			)
      Path(_SCREAMING_SNAKE_CASE			).open("""w"""			).writelines(_SCREAMING_SNAKE_CASE			)


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

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



class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     def        SCREAMING_SNAKE_CASE__						(							self		:					Any		,lowerCamelCase__		:					List[str] )  ->	List[Any]:




           '''simple docstring'''


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

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




           '''simple docstring'''


           self.run_eval_tester(lowerCamelCase__ )






     @parameterized.expand([BART_TINY, MBART_TINY] )
     @slow
     def        SCREAMING_SNAKE_CASE__						(							self		:					str		,lowerCamelCase__		:					Optional[Any] )  ->	Any:




           '''simple docstring'''


           self.run_eval_tester(lowerCamelCase__ )






     @parameterized.expand([T5_TINY, MBART_TINY] )
     @slow
     def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any]		,lowerCamelCase__		:					Tuple )  ->	List[str]:




           '''simple docstring'''


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

           SCREAMING_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!""",
               ],
           }

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









import pytest

from datasets import inspect_metric, list_metrics, load_metric



@pytest.fixture
def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     List[Any]:


      '''simple docstring'''


      monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings"""				,		set()			)



@pytest.fixture
def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     Dict:


      '''simple docstring'''


      class 	UpperCamelCase__				:



           '''simple docstring'''

           def __init__(							self		:					int		,lowerCamelCase__		:					Dict )  ->	List[Any]:




                 '''simple docstring'''


                 SCREAMING_SNAKE_CASE	=		metric_id

      class 	UpperCamelCase__				:



           '''simple docstring'''

           __snake_case					:			List[str]				=    [MetricMock(lowerCAmelCase_     ) for metric_id in ["accuracy", "mse", "precision", "codeparrot/apps_metric"]]






           def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int] )  ->	str:




                 '''simple docstring'''


                 return self._metrics
      monkeypatch.setattr("""datasets.inspect.huggingface_hub"""				,		HfhMock()			)



@pytest.mark.parametrize(
    """func, args"""				,		[(load_metric, ("""metrics/mse""",)), (list_metrics, ()), (inspect_metric, ("""metrics/mse""", """tmp_path"""))]			)
def      __lowercase     (   _SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)				->     Union[str, Any]:


      '''simple docstring'''


      if "tmp_path" in args:
            SCREAMING_SNAKE_CASE	=		tuple(arg if arg != """tmp_path""" else tmp_path for arg in args			)
      with pytest.warns(_SCREAMING_SNAKE_CASE				,		match="""https://huggingface.co/docs/evaluate"""			):
            func(*_SCREAMING_SNAKE_CASE			)


