

"""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


__A      		=     [
    {'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 				snake_case_(_UpperCamelCase=True					)							->     List[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=_UpperCamelCase					)					)
class   lowercase_   (  _UpperCamelCase					):
      UpperCamelCase_      :		List[Any]										=    None
      UpperCamelCase_      :		List[str]										=    None



      def 						UpperCamelCase_		(      self				:    Tuple      , A__				:    Any      , A__				:    str		)   ->					Optional[int]:
        with TemporaryDirectory() as tmp_dir:
          _snake_case						=							dataset_module_factory(_SCREAMING_SNAKE_CASE      , cache_dir=_SCREAMING_SNAKE_CASE		)

          _snake_case						=							import_main_class(dataset_module.module_path      , dataset=_SCREAMING_SNAKE_CASE		)

          _snake_case						=							builder_cls(
              cache_dir=_SCREAMING_SNAKE_CASE      , config_name=_SCREAMING_SNAKE_CASE      , hash=dataset_module.hash      , )

          _snake_case						=							'''/'''.join(
              [
                  HF_GCP_BASE_URL,
                  builder_instance._relative_data_dir(with_hash=_SCREAMING_SNAKE_CASE		).replace(os.sep      , '''/'''		),
                  config.DATASET_INFO_FILENAME,
              ]		)
          _snake_case						=							cached_path(_SCREAMING_SNAKE_CASE      , cache_dir=_SCREAMING_SNAKE_CASE		)
          self.assertTrue(os.path.exists(_SCREAMING_SNAKE_CASE		)		)



@pytest.mark.integration
def 				snake_case_(_UpperCamelCase					)							->     Optional[int]:



  """simple docstring"""






  _snake_case						=							tmp_path_factory.mktemp('''test_hf_gcp'''					) / '''test_wikipedia_simple'''
  _snake_case						=							dataset_module_factory('''wikipedia'''			,	cache_dir=_UpperCamelCase					)
  _snake_case						=							import_main_class(dataset_module.module_path					)
  _snake_case						=							builder_cls(
      cache_dir=_UpperCamelCase			,	config_name='''20220301.frr'''			,	hash=dataset_module.hash			,	)
  # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
  _snake_case						=							None
  builder_instance.download_and_prepare()
  _snake_case						=							builder_instance.as_dataset()
  assert ds



@pytest.mark.integration
def 				snake_case_(_UpperCamelCase					)							->     Dict:



  """simple docstring"""






  _snake_case						=							dataset_module_factory('''wikipedia'''			,	cache_dir=_UpperCamelCase					)
  _snake_case						=							import_main_class(dataset_module.module_path			,	dataset=_UpperCamelCase					)
  _snake_case						=							builder_cls(
      cache_dir=_UpperCamelCase			,	config_name='''20220301.frr'''			,	hash=dataset_module.hash			,	)
  _snake_case						=							builder_instance.as_streaming_dataset()
  assert ds
  assert isinstance(_UpperCamelCase			,	_UpperCamelCase					)
  assert "train" in ds
  assert isinstance(ds['''train''']			,	_UpperCamelCase					)
  assert next(iter(ds['''train''']					)					)




def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase					)							->     str:



  """simple docstring"""






  if a < 0 or b < 0:
    raise ValueError('''the value of both inputs must be positive'''					)
  _snake_case						=							str(bin(_UpperCamelCase					)					)[2:]  # remove the leading "0b"
  _snake_case						=							str(bin(_UpperCamelCase					)					)[2:]
  _snake_case						=							max(len(_UpperCamelCase					)			,	len(_UpperCamelCase					)					)
  return "0b" + "".join(
      str(int('''1''' in (char_a, char_b)					)					)
      for char_a, char_b in zip(a_binary.zfill(_UpperCamelCase					)			,	b_binary.zfill(_UpperCamelCase					)					)					)


if __name__ == "__main__":
 import doctest

 doctest.testmod()

