


'''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)
UpperCAmelCase__  			=				logging.getLogger()






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Path,_SCREAMING_SNAKE_CASE					: list ):






			"""simple docstring"""




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


UpperCAmelCase__  			=				'''patrickvonplaten/t5-tiny-random'''
UpperCAmelCase__  			=				'''sshleifer/bart-tiny-random'''
UpperCAmelCase__  			=				'''sshleifer/tiny-mbart'''

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






class 						a__					(					a_   ):





			'''simple docstring'''

			def 					lowerCAmelCase     (  self							:			Tuple			,    lowerCAmelCase_							:			Dict	)      ->		Dict:
						__A=	Path(self.get_auto_remove_tmp_dir()	) / 'utest_input.source'
						__A=	input_file_name.parent / 'utest_output.txt'
						assert not output_file_name.exists()
						__A=	[' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
						_dump_articles(lowerCAmelCase_			,    lowerCAmelCase_	)

						__A=	str(Path(self.get_auto_remove_tmp_dir()	) / 'scores.json'	)
						__A=	'translation_en_to_de' if model == T5_TINY else 'summarization'
						__A=	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 					lowerCAmelCase     (  self							:			Tuple	)      ->		Union[str, Any]:
						self.run_eval_tester(lowerCAmelCase_	)
			@parameterized.expand([BART_TINY, MBART_TINY]	)
			@slow
			def 					lowerCAmelCase     (  self							:			Optional[Any]			,    lowerCAmelCase_							:			Dict	)      ->		Optional[int]:
						self.run_eval_tester(lowerCAmelCase_	)

			@parameterized.expand([T5_TINY, MBART_TINY]	)
			@slow
			def 					lowerCAmelCase     (  self							:			List[Any]			,    lowerCAmelCase_							:			Union[str, Any]	)      ->		Tuple:
						__A=	Path(self.get_auto_remove_tmp_dir()	) / 'utest_input.source'
						__A=	input_file_name.parent / 'utest_output.txt'
						assert not output_file_name.exists()

						__A=	{
						    '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!',
						    ],
						}

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







'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


UpperCAmelCase__  			=				{
    '''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TrOCRConfig'''],
    '''processing_trocr''': ['''TrOCRProcessor'''],
}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__  			=				[
					    '''TROCR_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TrOCRForCausalLM''',
					    '''TrOCRPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
					from .processing_trocr import TrOCRProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
					import sys

					UpperCAmelCase__  			=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



