


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    =       logging.getLogger()






def 			UpperCamelCase (     __magic_name__					:							Path   ,   __magic_name__					:							list					)       ->  Any:
		"""simple docstring"""




		lowercase__					      =		"""\n""".join(snake_case_					)
		Path(snake_case_					).open("""w"""					).writelines(snake_case_					)


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

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







class 							A   (	_UpperCAmelCase							):
					'''simple docstring'''






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




							"""simple docstring"""


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

							lowercase__					      =		str(Path(self.get_auto_remove_tmp_dir()		) / """scores.json"""		)
							lowercase__					      =		"""translation_en_to_de""" if model == T5_TINY else """summarization"""
							lowercase__					      =		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(SCREAMING_SNAKE_CASE_				, """argv"""				, SCREAMING_SNAKE_CASE_		):
									run_generate()
									assert Path(SCREAMING_SNAKE_CASE_		).exists()
									# os.remove(Path(output_file_name))

					def   lowerCamelCase__					(self   :						Optional[Any]		)						->       int:




							"""simple docstring"""


							self.run_eval_tester(SCREAMING_SNAKE_CASE_		)

					@parameterized.expand([BART_TINY, MBART_TINY]		)
					@slow
					def   lowerCamelCase__					(self   :						Any				, _UpperCAmelCase   :						Dict		)						->       Tuple:




							"""simple docstring"""


							self.run_eval_tester(SCREAMING_SNAKE_CASE_		)


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




							"""simple docstring"""


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

							lowercase__					      =		{
							    """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__					      =		Path(self.get_auto_remove_tmp_dir()		)
							lowercase__					      =		str(tmp_dir / """scores.json"""		)
							lowercase__					      =		str(tmp_dir / """val.target"""		)
							_dump_articles(SCREAMING_SNAKE_CASE_				, text["""en"""]		)
							_dump_articles(SCREAMING_SNAKE_CASE_				, text["""de"""]		)
							lowercase__					      =		"""translation_en_to_de""" if model == T5_TINY else """summarization"""
							lowercase__					      =		f'''\n            run_eval_search.py\n            {model}\n            {str(SCREAMING_SNAKE_CASE_		)}\n            {str(SCREAMING_SNAKE_CASE_		)}\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(SCREAMING_SNAKE_CASE_				, """argv"""				, SCREAMING_SNAKE_CASE_		):
									with CaptureStdout() as cs:
											run_search()
									lowercase__					      =		[""" num_beams | length_penalty""", model, """Best score args"""]
									lowercase__					      =		["""Info"""]
									if "translation" in task:
											expected_strings.append("""bleu"""		)
									else:
											expected_strings.extend(SCREAMING_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(SCREAMING_SNAKE_CASE_		).exists()
									os.remove(Path(SCREAMING_SNAKE_CASE_		)		)





def 			UpperCamelCase (     __magic_name__					:							str   ,   __magic_name__					:							str					)       ->  list:
		"""simple docstring"""




		lowercase__					      =		len(__magic_name__					)
		lowercase__					      =		[]
		for i in range(len(__magic_name__					) - pat_len + 1					):
				lowercase__					      =		True
				for j in range(__magic_name__					):
						if s[i + j] != pattern[j]:
								lowercase__					      =		False
								break
				if match_found:
						position.append(__magic_name__					)
		return position


if __name__ == "__main__":
	assert naive_pattern_search('ABCDEFG', 'DE') == [3]
	print(naive_pattern_search('ABAAABCDBBABCDDEBCABC', 'ABC'))

