






'''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:      Dict  				=				logging.getLogger()






def 	_UpperCAmelCase    (  a		:	str						,			a		:	Optional[int]							)			->			List[str]:





						"""simple docstring"""
						lowercase_      :   Tuple        =			'\n'.join(__snake_case							)
						Path(__snake_case							).open('w'							).writelines(__snake_case							)


A:      Any  				=				"patrickvonplaten/t5-tiny-random"
A:      Tuple  				=				"sshleifer/bart-tiny-random"
A:      Dict  				=				"sshleifer/tiny-mbart"

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






class 							__magic_name__     (	UpperCAmelCase_				):







	"""simple docstring"""



	def        lowerCamelCase__		(							self  ,      _lowercase       )						->  Union[str, Any]:
							lowercase_      :   Optional[int]        =			Path(self.get_auto_remove_tmp_dir()       ) / 'utest_input.source'
							lowercase_      :   Union[str, Any]        =			input_file_name.parent / 'utest_output.txt'
							assert not output_file_name.exists()
							lowercase_      :   Dict        =			[' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
							_dump_articles(__a  ,      __a       )

							lowercase_      :   Union[str, Any]        =			str(Path(self.get_auto_remove_tmp_dir()       ) / 'scores.json'       )
							lowercase_      :   str        =			'translation_en_to_de' if model == T5_TINY else 'summarization'
							lowercase_      :   Any        =			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        lowerCamelCase__		(							self       )						->  List[str]:
							self.run_eval_tester(__a       )
	@parameterized.expand([BART_TINY, MBART_TINY]       )
	@slow
	def        lowerCamelCase__		(							self  ,      _lowercase       )						->  Optional[int]:
							self.run_eval_tester(__a       )







	@parameterized.expand([T5_TINY, MBART_TINY]       )
	@slow
	def        lowerCamelCase__		(							self  ,      _lowercase       )						->  List[str]:
							lowercase_      :   Dict        =			Path(self.get_auto_remove_tmp_dir()       ) / 'utest_input.source'
							lowercase_      :   Optional[int]        =			input_file_name.parent / 'utest_output.txt'
							assert not output_file_name.exists()

							lowercase_      :   int        =			{
							    '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!',
							    ],
							}

							lowercase_      :   Any        =			Path(self.get_auto_remove_tmp_dir()       )
							lowercase_      :   List[str]        =			str(tmp_dir / 'scores.json'       )
							lowercase_      :   List[Any]        =			str(tmp_dir / 'val.target'       )
							_dump_articles(__a  ,      text['en']       )
							_dump_articles(__a  ,      text['de']       )
							lowercase_      :   Any        =			'translation_en_to_de' if model == T5_TINY else 'summarization'
							lowercase_      :   Tuple        =			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()
													lowercase_      :   Union[str, Any]        =			[' num_beams | length_penalty', model, 'Best score args']
													lowercase_      :   Any        =			['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       )       )








'''simple docstring'''

from ..utils import DummyObject, requires_backends






class 							__magic_name__     (	metaclass=UpperCAmelCase_				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      str        =  ['transformers', 'torch', 'note_seq']
	def __init__(							self  ,      *_lowercase  ,      **_lowercase       )						->  Dict:
							requires_backends(self  ,      ['transformers', 'torch', 'note_seq']       )
	@classmethod
	def        lowerCamelCase__		(							cls  ,      *_lowercase  ,      **_lowercase       )						->  List[str]:
							requires_backends(cls  ,      ['transformers', 'torch', 'note_seq']       )







	@classmethod
	def        lowerCamelCase__		(							cls  ,      *_lowercase  ,      **_lowercase       )						->  Dict:
							requires_backends(cls  ,      ['transformers', 'torch', 'note_seq']       )
