

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    :       Any        =							[
    {"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__					(		UpperCAmelCase							:      Tuple=True      )  ->						Optional[Any]:
  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=lowerCamelCase__						)						)
class  __UpperCAmelCase					(	lowerCamelCase__						):
   UpperCamelCase       					=					None
   UpperCamelCase       					=					None



   def 	__magic_name__   (							self							:					int,		__A							:					Dict,		__A							:					Tuple						):
     with TemporaryDirectory() as tmp_dir:
       UpperCAmelCase	:							int						=			dataset_module_factory(__A,		cache_dir=__A						)

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

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

       UpperCAmelCase	:							str						=			'''/'''.join(
           [
               HF_GCP_BASE_URL,
               builder_instance._relative_data_dir(with_hash=__A						).replace(os.sep,		'''/'''						),
               config.DATASET_INFO_FILENAME,
           ]						)
       UpperCAmelCase	:							Optional[Any]						=			cached_path(__A,		cache_dir=__A						)
       self.assertTrue(os.path.exists(__A						)						)






@pytest.mark.integration
def       a__					(		UpperCAmelCase							:      Any      )  ->						List[str]:
  UpperCAmelCase	:							List[str]						=			tmp_path_factory.mktemp('''test_hf_gcp'''      ) / '''test_wikipedia_simple'''
  UpperCAmelCase	:							Any						=			dataset_module_factory('''wikipedia'''    ,			cache_dir=UpperCAmelCase      )
  UpperCAmelCase	:							List[str]						=			import_main_class(dataset_module.module_path      )
  UpperCAmelCase	:							DatasetBuilder						=			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
  UpperCAmelCase	:							Any						=			None
  builder_instance.download_and_prepare()
  UpperCAmelCase	:							Dict						=			builder_instance.as_dataset()
  assert ds






@pytest.mark.integration
def       a__					(		UpperCAmelCase							:      List[Any]      )  ->						List[Any]:
  UpperCAmelCase	:							Dict						=			dataset_module_factory('''wikipedia'''    ,			cache_dir=UpperCAmelCase      )
  UpperCAmelCase	:							int						=			import_main_class(dataset_module.module_path    ,			dataset=UpperCAmelCase      )
  UpperCAmelCase	:							DatasetBuilder						=			builder_cls(
      cache_dir=UpperCAmelCase    ,			config_name='''20220301.frr'''    ,			hash=dataset_module.hash    ,			)
  UpperCAmelCase	:							Any						=			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       a__					(		UpperCAmelCase							:      int    ,			UpperCAmelCase							:      int      )  ->						str:
  if a < 0 or b < 0:
    raise ValueError('''the value of both inputs must be positive'''      )
  UpperCAmelCase	:							List[Any]						=			str(bin(UpperCAmelCase      )      )[2:]  # remove the leading "0b"
  UpperCAmelCase	:							List[str]						=			str(bin(UpperCAmelCase      )      )[2:]
  UpperCAmelCase	:							Optional[Any]						=			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()





