


'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


__snake_case				 =	[
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.de'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.en'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.fr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.frr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.it'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.simple'''},
    {'''dataset''': '''snli''', '''config_name''': '''plain_text'''},
    {'''dataset''': '''eli5''', '''config_name''': '''LFQA_reddit'''},
    {'''dataset''': '''wiki40b''', '''config_name''': '''en'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.compressed'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.no_index'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.multiset.no_index'''},
    {'''dataset''': '''natural_questions''', '''config_name''': '''default'''},
]


def      a (     __a=True  )    ->      Union[str, Any]:



					'''simple docstring'''






					if with_config:
										return [
										    {
										        "testcase_name": d["dataset"] + "/" + d["config_name"],
										        "dataset": d["dataset"],
										        "config_name": d["config_name"],
										    }
										    for d in DATASETS_ON_HF_GCP
										]
					else:
										return [
										    {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
										]
@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=A__   )   )
class   lowercase      (				A__   ):

		"""simple docstring"""

		_a       					=							None
		_a       					=							None




		def        lowerCAmelCase__							(						self       ,  UpperCamelCase_       ,  UpperCamelCase_				):

							'''simple docstring'''


							with TemporaryDirectory() as tmp_dir:
												UpperCamelCase__  :Optional[Any]				   =					dataset_module_factory(UpperCamelCase_       ,  cache_dir=UpperCamelCase_				)

												UpperCamelCase__  :int				   =					import_main_class(dataset_module.module_path       ,  dataset=UpperCamelCase_				)

												UpperCamelCase__  :DatasetBuilder				   =					builder_cls(
												    cache_dir=UpperCamelCase_       ,  config_name=UpperCamelCase_       ,  hash=dataset_module.hash       ,  )

												UpperCamelCase__  :Dict				   =					'''/'''.join(
												    [
												        HF_GCP_BASE_URL,
												        builder_instance._relative_data_dir(with_hash=UpperCamelCase_				).replace(os.sep       ,  '''/'''				),
												        config.DATASET_INFO_FILENAME,
												    ]				)
												UpperCamelCase__  :Optional[int]				   =					cached_path(UpperCamelCase_       ,  cache_dir=UpperCamelCase_				)
												self.assertTrue(os.path.exists(UpperCamelCase_				)				)



@pytest.mark.integration
def      a (     __a  )    ->      int:



					'''simple docstring'''






					UpperCamelCase__  :Union[str, Any]				   =					tmp_path_factory.mktemp('''test_hf_gcp'''  ) / '''test_wikipedia_simple'''
					UpperCamelCase__  :int				   =					dataset_module_factory('''wikipedia'''					,   cache_dir=__a  )
					UpperCamelCase__  :Optional[Any]				   =					import_main_class(dataset_module.module_path  )
					UpperCamelCase__  :DatasetBuilder				   =					builder_cls(
					    cache_dir=__a					,   config_name='''20220301.frr'''					,   hash=dataset_module.hash					,   )
					# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
					UpperCamelCase__  :Tuple				   =					None
					builder_instance.download_and_prepare()
					UpperCamelCase__  :Any				   =					builder_instance.as_dataset()
					assert ds







@pytest.mark.integration
def      a (     __a  )    ->      List[Any]:



					'''simple docstring'''






					UpperCamelCase__  :str				   =					dataset_module_factory('''wikipedia'''					,   cache_dir=__a  )
					UpperCamelCase__  :int				   =					import_main_class(dataset_module.module_path					,   dataset=__a  )
					UpperCamelCase__  :DatasetBuilder				   =					builder_cls(
					    cache_dir=__a					,   config_name='''20220301.frr'''					,   hash=dataset_module.hash					,   )
					UpperCamelCase__  :Any				   =					builder_instance.as_streaming_dataset()
					assert ds
					assert isinstance(__a					,   __a  )
					assert "train" in ds
					assert isinstance(ds['''train''']					,   __a  )
					assert next(iter(ds['''train''']  )  )



'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels