
'''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


UpperCAmelCase_							: Tuple =							[
    {'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_							(						_lowerCAmelCase :     Optional[Any]=True				):



      """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 			UpperCAmelCase__    (							A			):
    lowerCAmelCase_					     =		None
    lowerCAmelCase_					     =		None



    def 	lowerCamelCase_	(						self   :							Union[str, Any],__A   :							str,__A   :							int  ):
          with TemporaryDirectory() as tmp_dir:
                _lowerCamelCase					: Union[str, Any]		    = dataset_module_factory(__A,cache_dir=__A  )

                _lowerCamelCase					: Any		    = import_main_class(dataset_module.module_path,dataset=__A  )

                _lowerCamelCase					: DatasetBuilder		    = builder_cls(
                    cache_dir=__A,config_name=__A,hash=dataset_module.hash,)

                _lowerCamelCase					: List[Any]		    = "/".join(
                    [
                        HF_GCP_BASE_URL,
                        builder_instance._relative_data_dir(with_hash=__A  ).replace(os.sep,"/"  ),
                        config.DATASET_INFO_FILENAME,
                    ]  )
                _lowerCamelCase					: Any		    = cached_path(__A,cache_dir=__A  )
                self.assertTrue(os.path.exists(__A  )  )







@pytest.mark.integration
def 		A_							(						_lowerCAmelCase :     Tuple				):



      """simple docstring"""




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







@pytest.mark.integration
def 		A_							(						_lowerCAmelCase :     str				):



      """simple docstring"""




      _lowerCamelCase					: List[Any]		    = dataset_module_factory("wikipedia"					,						cache_dir=_lowerCAmelCase				)
      _lowerCamelCase					: Optional[int]		    = import_main_class(dataset_module.module_path					,						dataset=_lowerCAmelCase				)
      _lowerCamelCase					: DatasetBuilder		    = builder_cls(
          cache_dir=_lowerCAmelCase					,						config_name="20220301.frr"					,						hash=dataset_module.hash					,						)
      _lowerCamelCase					: str		    = builder_instance.as_streaming_dataset()
      assert ds
      assert isinstance(_lowerCAmelCase					,						_lowerCAmelCase				)
      assert "train" in ds
      assert isinstance(ds["train"]					,						_lowerCAmelCase				)
      assert next(iter(ds["train"]				)				)
"""simple docstring"""




def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		return abs(lowerCamelCase__  ) if a == 0 else greatest_common_divisor(b % a      ,	lowerCamelCase__  )







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		while y:  # --> when y=0 then loop will terminate and return x as final GCD.
				lowerCAmelCase__ ,       lowerCAmelCase__   = y, x % y
		return abs(lowerCamelCase__  )







def 				_UpperCAmelCase		(							):





		"""simple docstring"""




		try:
				lowerCAmelCase__   = input("""Enter two integers separated by comma (,): """  ).split(""","""  )
				lowerCAmelCase__   = int(nums[0]  )
				lowerCAmelCase__   = int(nums[1]  )
				print(
				    f"""greatest_common_divisor({num_a}, {num_a}) = """
				    f"""{greatest_common_divisor(lowerCamelCase__      ,	lowerCamelCase__  )}"""  )
				print(f"""By iterative gcd({num_a}, {num_a}) = {gcd_by_iterative(lowerCamelCase__      ,	lowerCamelCase__  )}"""  )
		except (IndexError, UnboundLocalError, ValueError):
				print("""Wrong input"""  )


if __name__ == "__main__":
			main()




