




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)
snake_case_ : str    		=       logging.getLogger()


def    A						(__A   :    Path   ,				__A   :    list       )   ->      Tuple:







     """simple docstring"""


     UpperCAmelCase_          =							'''\n'''.join(__A       )
     Path(__A       ).open('''w'''       ).writelines(__A       )


snake_case_ : Union[str, Any]    		=       "patrickvonplaten/t5-tiny-random"
snake_case_ : int    		=       "sshleifer/bart-tiny-random"
snake_case_ : List[str]    		=       "sshleifer/tiny-mbart"

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







class __snake_case			(			a		):







   def lowerCamelCase						(      self		:						List[str]					,						_snake_case		:						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_          =							[''' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.''']
        _dump_articles(_snake_case					,						_snake_case)

        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(_snake_case					,						'''argv'''					,						_snake_case):
             run_generate()
             assert Path(_snake_case).exists()
             # os.remove(Path(output_file_name))







   def lowerCamelCase						(      self		:						Tuple):

        """simple docstring"""


        self.run_eval_tester(_snake_case)







   @parameterized.expand([BART_TINY, MBART_TINY])
   @slow
   def lowerCamelCase						(      self		:						List[Any]					,						_snake_case		:						Tuple):

        """simple docstring"""


        self.run_eval_tester(_snake_case)







   @parameterized.expand([T5_TINY, MBART_TINY])
   @slow
   def lowerCamelCase						(      self		:						str					,						_snake_case		:						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_          =							{
            '''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(_snake_case					,						text['''en'''])
        _dump_articles(_snake_case					,						text['''de'''])
        UpperCAmelCase_          =							'''translation_en_to_de''' if model == T5_TINY else '''summarization'''
        UpperCAmelCase_          =							F"""
            run_eval_search.py
            {model}
            {str(_snake_case)}
            {str(_snake_case)}
            --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(_snake_case					,						'''argv'''					,						_snake_case):
             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(_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(_snake_case).exists()
             os.remove(Path(_snake_case))












from diffusers.utils.testing_utils import require_onnxruntime







@require_onnxruntime
class __snake_case			:
   pass






