



"""simple docstring"""





import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict




@pytest.mark.parametrize(
    'files'     ,				[
        ['full:README.md', 'dataset_infos.json'],
        ['empty:README.md', 'dataset_infos.json'],
        ['dataset_infos.json'],
        ['full:README.md'],
    ]     ,				)
def 	UpperCAmelCase     (		A	:						str     ,				A	:						Optional[int]       ):

							'''simple docstring'''


							_UpperCAmelCase							 =		tmp_path_factory.mktemp('dset_infos_dir'       )
							if "full:README.md" in files:
														with open(dataset_infos_dir / 'README.md'     ,				'w'       ) as f:
																					f.write('---\ndataset_info:\n  dataset_size: 42\n---'       )
							if "empty:README.md" in files:
														with open(dataset_infos_dir / 'README.md'     ,				'w'       ) as f:
																					f.write(''       )
    # we want to support dataset_infos.json for backward compatibility
							if "dataset_infos.json" in files:
														with open(dataset_infos_dir / 'dataset_infos.json'     ,				'w'       ) as f:
																					f.write('{"default": {"dataset_size": 42}}'       )
							_UpperCAmelCase							 =		DatasetInfosDict.from_directory(A       )
							assert dataset_infos
							assert dataset_infos["default"].dataset_size == 42




@pytest.mark.parametrize(
    'dataset_info'     ,				[
        DatasetInfo(),
        DatasetInfo(
            description='foo'     ,				features=Features({'a': Value('int32'       )}       )     ,				builder_name='builder'     ,				config_name='config'     ,				version='1.0.0'     ,				splits=[{'name': 'train'}]     ,				download_size=42     ,				),
    ]     ,				)
def 	UpperCAmelCase     (		A	:						str     ,				A	:						DatasetInfo       ):

							'''simple docstring'''


							_UpperCAmelCase							 =		str(A       )
							dataset_info.write_to_directory(A       )
							_UpperCAmelCase							 =		DatasetInfo.from_directory(A       )
							assert dataset_info == reloaded
							assert os.path.exists(os.path.join(A     ,				'dataset_info.json'       )       )




def 	UpperCAmelCase     (		):

							'''simple docstring'''


							_UpperCAmelCase							 =		DatasetInfo(
							    description='foo'     ,				citation='bar'     ,				homepage='https://foo.bar'     ,				license='CC0'     ,				features=Features({'a': Value('int32'       )}       )     ,				post_processed={}     ,				supervised_keys=()     ,				task_templates=[]     ,				builder_name='builder'     ,				config_name='config'     ,				version='1.0.0'     ,				splits=[{'name': 'train', 'num_examples': 42}]     ,				download_checksums={}     ,				download_size=1337     ,				post_processing_size=442     ,				dataset_size=1234     ,				size_in_bytes=1337 + 442 + 1234     ,				)
							_UpperCAmelCase							 =		dataset_info._to_yaml_dict()
							assert sorted(A       ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML       )
							for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
														assert key in dataset_info_yaml_dict
														assert isinstance(dataset_info_yaml_dict[key]     ,				(list, dict, int, str)       )
							_UpperCAmelCase							 =		yaml.safe_dump(A       )
							_UpperCAmelCase							 =		yaml.safe_load(A       )
							assert dataset_info_yaml_dict == reloaded




def 	UpperCAmelCase     (		):

							'''simple docstring'''


							_UpperCAmelCase							 =		DatasetInfo()
							_UpperCAmelCase							 =		dataset_info._to_yaml_dict()
							assert dataset_info_yaml_dict == {}






@pytest.mark.parametrize(
    'dataset_infos_dict'     ,				[
        DatasetInfosDict(),
        DatasetInfosDict({'default': DatasetInfo()}       ),
        DatasetInfosDict({'my_config_name': DatasetInfo()}       ),
        DatasetInfosDict(
            {
                'default': DatasetInfo(
                    description='foo'     ,				features=Features({'a': Value('int32'       )}       )     ,				builder_name='builder'     ,				config_name='config'     ,				version='1.0.0'     ,				splits=[{'name': 'train'}]     ,				download_size=42     ,				)
            }       ),
        DatasetInfosDict(
            {
                'v1': DatasetInfo(dataset_size=42       ),
                'v2': DatasetInfo(dataset_size=1337       ),
            }       ),
    ]     ,				)
def 	UpperCAmelCase     (		A	:						Tuple     ,				A	:						DatasetInfosDict       ):

							'''simple docstring'''


							_UpperCAmelCase							 =		str(A       )
							dataset_infos_dict.write_to_directory(A       )
							_UpperCAmelCase							 =		DatasetInfosDict.from_directory(A       )

							# the config_name of the dataset_infos_dict take over the attribute
							for config_name, dataset_info in dataset_infos_dict.items():
														_UpperCAmelCase							 =		config_name
														# the yaml representation doesn't include fields like description or citation
														# so we just test that we can recover what we can from the yaml
														_UpperCAmelCase							 =		DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()       )
							assert dataset_infos_dict == reloaded

							if dataset_infos_dict:
														assert os.path.exists(os.path.join(A     ,				'README.md'       )       )







"""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)
lowercase  							=					logging.getLogger()




def 	UpperCAmelCase     (		A	:						Path     ,				A	:						list       ):

		'''simple docstring'''


		_UpperCAmelCase							 =		'\n'.join(A       )
		Path(A       ).open('w'       ).writelines(A       )


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 			lowercase__			(      A    ):
							'''simple docstring'''







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

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






							def        lowerCamelCase_   (  self						)			->							str:
									self.run_eval_tester(snake_case						)






							@parameterized.expand([BART_TINY, MBART_TINY]						)
							@slow
							def        lowerCamelCase_   (  self	,       snake_case						)			->							List[Any]:
									self.run_eval_tester(snake_case						)






							@parameterized.expand([T5_TINY, MBART_TINY]						)
							@slow
							def        lowerCamelCase_   (  self	,       snake_case						)			->							Dict:
									_UpperCAmelCase							 =		Path(self.get_auto_remove_tmp_dir()						) / 'utest_input.source'
									_UpperCAmelCase							 =		input_file_name.parent / 'utest_output.txt'
									assert not output_file_name.exists()

									_UpperCAmelCase							 =		{
									    '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!',
									    ],
									}

									_UpperCAmelCase							 =		Path(self.get_auto_remove_tmp_dir()						)
									_UpperCAmelCase							 =		str(tmp_dir / 'scores.json'						)
									_UpperCAmelCase							 =		str(tmp_dir / 'val.target'						)
									_dump_articles(snake_case	,       text['en']						)
									_dump_articles(snake_case	,       text['de']						)
									_UpperCAmelCase							 =		'translation_en_to_de' if model == T5_TINY else 'summarization'
									_UpperCAmelCase							 =		f'\n            run_eval_search.py\n            {model}\n            {str(snake_case						)}\n            {str(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(snake_case	,       'argv'	,       snake_case						):
											with CaptureStdout() as cs:
													run_search()
											_UpperCAmelCase							 =		[' num_beams | length_penalty', model, 'Best score args']
											_UpperCAmelCase							 =		['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						)						)


