




'''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)
a    :							str										=    logging.getLogger()


def 						__magic_name__       (      __UpperCAmelCase, __UpperCAmelCase      )						->   Optional[Any]:

					'''simple docstring'''

					snake_case_		     =							'''\n'''.join(__UpperCAmelCase      )
					Path(__UpperCAmelCase      ).open('''w'''      ).writelines(__UpperCAmelCase      )


a    :							Union[str, Any]										=    'patrickvonplaten/t5-tiny-random'
a    :							Dict										=    'sshleifer/bart-tiny-random'
a    :							List[str]										=    'sshleifer/tiny-mbart'

a    :							List[str]										=    logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks






class 		a							(  _lowerCamelCase	):


				def     A_					(						self       :   int			,							lowercase_       :   Tuple   ):
									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(lowercase_			,							lowercase_   )

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


				def     A_					(						self       :   Any   ):
									self.run_eval_tester(lowercase_   )


				@parameterized.expand([BART_TINY, MBART_TINY]   )
				@slow
				def     A_					(						self       :   Union[str, Any]			,							lowercase_       :   int   ):
									self.run_eval_tester(lowercase_   )


				@parameterized.expand([T5_TINY, MBART_TINY]   )
				@slow
				def     A_					(						self       :   Any			,							lowercase_       :   Dict   ):
									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(lowercase_			,							text['''en''']   )
									_dump_articles(lowercase_			,							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(lowercase_   )}\n            {str(lowercase_   )}\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(lowercase_			,							'''argv'''			,							lowercase_   ):
														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(lowercase_   )
														for w in expected_strings:
																			assert w in cs.out
														for w in un_expected_strings:
																			assert w not in cs.out
														assert Path(lowercase_   ).exists()
														os.remove(Path(lowercase_   )   )







'''simple docstring'''

from ....utils import logging


a    :							Optional[int]										=    logging.get_logger(__name__)






class 		a							(  _lowerCamelCase	):


				def __init__(						self       :   int			,							lowercase_       :   Tuple			,							lowercase_       :   Any=None			,							lowercase_       :   List[Any]=2048   ):
									snake_case_		     =							config.__dict__
									snake_case_		     =							modal_hidden_size
									if num_labels:
														snake_case_		     =							num_labels

