



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)
lowercase_													=      logging.getLogger()






def        __lowerCAmelCase		(	__lowerCamelCase						:     Path					, __lowerCamelCase						:     list						)	->    Union[str, Any]:
					__lowerCAmelCase						 ="""\n""".join(__lowerCamelCase						)
					Path(__lowerCamelCase						).open("""w"""						).writelines(__lowerCamelCase						)


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

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






class     __a			(  SCREAMING_SNAKE_CASE					):



	def 		UpperCamelCase				(    self				:     str					,						snake_case_				:     List[str])->				str:
						__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(snake_case_					,						snake_case_)

						__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(snake_case_					,						"""argv"""					,						snake_case_):
											run_generate()
											assert Path(snake_case_).exists()
											# os.remove(Path(output_file_name))



	def 		UpperCamelCase				(    self				:     Union[str, Any])->				Union[str, Any]:
						self.run_eval_tester(snake_case_)



	@parameterized.expand([BART_TINY, MBART_TINY])
	@slow
	def 		UpperCamelCase				(    self				:     Any					,						snake_case_				:     int)->				Optional[Any]:
						self.run_eval_tester(snake_case_)



	@parameterized.expand([T5_TINY, MBART_TINY])
	@slow
	def 		UpperCamelCase				(    self				:     List[str]					,						snake_case_				:     int)->				Tuple:
						__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(snake_case_					,						text["""en"""])
						_dump_articles(snake_case_					,						text["""de"""])
						__lowerCAmelCase						 ="""translation_en_to_de""" if model == T5_TINY else """summarization"""
						__lowerCAmelCase						 =F"""
            run_eval_search.py
            {model}
            {str(snake_case_)}
            {str(snake_case_)}
            --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(snake_case_					,						"""argv"""					,						snake_case_):
											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(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(snake_case_).exists()
											os.remove(Path(snake_case_))









import pytest


lowercase_													=      '''__dummy_dataset1__'''

lowercase_													=      '''
import json
import os

import datasets


REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = {"train": REPO_URL + "wikiann-bn-train.jsonl", "validation": REPO_URL + "wikiann-bn-validation.jsonl"}


class __DummyDataset1__(datasets.GeneratorBasedBuilder):

    def _info(self):
        features = datasets.Features(
            {
                "tokens": datasets.Sequence(datasets.Value("string")),
                "ner_tags": datasets.Sequence(
                    datasets.features.ClassLabel(
                        names=[
                            "O",
                            "B-PER",
                            "I-PER",
                            "B-ORG",
                            "I-ORG",
                            "B-LOC",
                            "I-LOC",
                        ]
                    )
                ),
                "langs": datasets.Sequence(datasets.Value("string")),
                "spans": datasets.Sequence(datasets.Value("string")),
            }
        )
        return datasets.DatasetInfo(features=features)

    def _split_generators(self, dl_manager):
        dl_path = dl_manager.download(URLS)
        return [
            datasets.SplitGenerator(datasets.Split.TRAIN, gen_kwargs={"filepath": dl_path["train"]}),
            datasets.SplitGenerator(datasets.Split.VALIDATION, gen_kwargs={"filepath": dl_path["validation"]}),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, "r", encoding="utf-8") as f:
            for i, line in enumerate(f):
                yield i, json.loads(line)
'''






@pytest.fixture
def        __lowerCAmelCase		(	)	->    Any:
					return DATASET_LOADING_SCRIPT_NAME






@pytest.fixture
def        __lowerCAmelCase		(	)	->    Union[str, Any]:
					return DATASET_LOADING_SCRIPT_CODE






@pytest.fixture
def        __lowerCAmelCase		(	__lowerCamelCase						:     Optional[Any]					, __lowerCamelCase						:     Tuple					, __lowerCamelCase						:     str						)	->    List[str]:
					__lowerCAmelCase						 =dataset_loading_script_name
					__lowerCAmelCase						 =tmp_path / """datasets""" / script_name
					script_dir.mkdir(parents=__lowerCamelCase						)
					__lowerCAmelCase						 =script_dir / f"""{script_name}.py"""
					with open(__lowerCamelCase					, """w"""						) as f:
										f.write(__lowerCamelCase						)
					return str(__lowerCamelCase						)




