


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


lowerCAmelCase							=						[
    {"""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 						__SCREAMING_SNAKE_CASE       (					lowercase_=True			)		->    List[str]:




						'''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=_UpperCamelCase   )   )
class        lowerCamelCase      (     _UpperCamelCase   ):
	_lowerCAmelCase    :		List[str]        =	None
	_lowerCAmelCase    :		List[str]        =	None


	def    A(						self							,    lowercase__							,    lowercase__):
							with TemporaryDirectory() as tmp_dir:
													__UpperCAmelCase :       Tuple  						=  dataset_module_factory(lowercase__							,    cache_dir=lowercase__)

													__UpperCAmelCase :       Optional[int]  						=  import_main_class(dataset_module.module_path							,    dataset=lowercase__)

													__UpperCAmelCase :       DatasetBuilder  						=  builder_cls(
													    cache_dir=lowercase__							,    config_name=lowercase__							,    hash=dataset_module.hash							,    )

													__UpperCAmelCase :       str  						=  '''/'''.join(
													    [
													        HF_GCP_BASE_URL,
													        builder_instance._relative_data_dir(with_hash=lowercase__).replace(os.sep							,    '''/'''),
													        config.DATASET_INFO_FILENAME,
													    ])
													__UpperCAmelCase :       List[str]  						=  cached_path(lowercase__							,    cache_dir=lowercase__)
													self.assertTrue(os.path.exists(lowercase__))






@pytest.mark.integration
def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    List[str]:




						'''simple docstring'''







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





@pytest.mark.integration
def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    Optional[int]:




						'''simple docstring'''







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





from __future__ import annotations




def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    int:




						'''simple docstring'''







						if not nums:
												return 0
						__UpperCAmelCase :       int  						=  nums[0]
						__UpperCAmelCase :       Optional[Any]  						=  0
						for num in nums[1:]:
												__UpperCAmelCase						,			__UpperCAmelCase :       int  						=  (
												    max_excluding + num,
												    max(lowercase_			,					lowercase_			),
												)
						return max(lowercase_			,					lowercase_			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()

