
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      lowerCamelCase__       (       __lowerCAmelCase						:						Path					,							__lowerCAmelCase						:						list       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			"\n".join(__lowerCAmelCase       )
			Path(__lowerCAmelCase       ).open("w"       ).writelines(__lowerCAmelCase       )


_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 			_lowerCAmelCase      (			__a ):




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

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




				def   __a		(      self  )       ->   Union[str, Any]:
							self.run_eval_tester(_UpperCamelCase  )




				@parameterized.expand([BART_TINY, MBART_TINY]  )
				@slow
				def   __a		(      self       ,       _UpperCamelCase  )       ->   str:
							self.run_eval_tester(_UpperCamelCase  )




				@parameterized.expand([T5_TINY, MBART_TINY]  )
				@slow
				def   __a		(      self       ,       _UpperCamelCase  )       ->   Optional[Any]:
							lowerCAmelCase_      			=			Path(self.get_auto_remove_tmp_dir()  ) / "utest_input.source"
							lowerCAmelCase_      			=			input_file_name.parent / "utest_output.txt"
							assert not output_file_name.exists()

							lowerCAmelCase_      			=			{
							    "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!",
							    ],
							}

							lowerCAmelCase_      			=			Path(self.get_auto_remove_tmp_dir()  )
							lowerCAmelCase_      			=			str(tmp_dir / "scores.json"  )
							lowerCAmelCase_      			=			str(tmp_dir / "val.target"  )
							_dump_articles(_UpperCamelCase       ,       text["en"]  )
							_dump_articles(_UpperCamelCase       ,       text["de"]  )
							lowerCAmelCase_      			=			"translation_en_to_de" if model == T5_TINY else "summarization"
							lowerCAmelCase_      			=			f"""
            run_eval_search.py
            {model}
            {str(_UpperCamelCase  )}
            {str(_UpperCamelCase  )}
            --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(_UpperCamelCase       ,       "argv"       ,       _UpperCamelCase  ):
										with CaptureStdout() as cs:
													run_search()
										lowerCAmelCase_      			=			[" num_beams | length_penalty", model, "Best score args"]
										lowerCAmelCase_      			=			["Info"]
										if "translation" in task:
													expected_strings.append("bleu"  )
										else:
													expected_strings.extend(_UpperCamelCase  )
										for w in expected_strings:
													assert w in cs.out
										for w in un_expected_strings:
													assert w not in cs.out
										assert Path(_UpperCamelCase  ).exists()
										os.remove(Path(_UpperCamelCase  )  )





import functools






def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			len(__lowerCAmelCase       )
			lowerCAmelCase_      			=			len(__lowerCAmelCase       )

			@functools.cache
			def min_distance(__lowerCAmelCase						:						int					,							__lowerCAmelCase						:						int       ) -> int:
						# if first word index is overflow - delete all from the second word
						if indexa >= len_worda:
									return len_worda - indexa
						# if second word index is overflow - delete all from the first word
						if indexa >= len_worda:
									return len_worda - indexa
						lowerCAmelCase_      			=			int(worda[indexa] != worda[indexa]       )  # current letters not identical
						return min(
						    1 + min_distance(indexa + 1					,							__lowerCAmelCase       )					,							1 + min_distance(__lowerCAmelCase					,							indexa + 1       )					,							diff + min_distance(indexa + 1					,							indexa + 1       )					,							)

			return min_distance(0					,							0       )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



