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_           =				[
    {'''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    lowerCAmelCase_  (		lowercase:				Dict=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=__a     )     )
class 			__magic_name__	(		__a     ):





   """simple docstring"""




   lowerCAmelCase   :     List[str]	      = None
   lowerCAmelCase   :     Union[str, Any]	      = None



   def 	lowerCAmelCase    (						self       :	List[Any]		,	_lowercase       :	int		,	_lowercase       :	int				):



    """simple docstring"""



    with TemporaryDirectory() as tmp_dir:
     _UpperCamelCase:  int    						=			dataset_module_factory(_lowercase		,	cache_dir=_lowercase				)

     _UpperCamelCase:  Dict    						=			import_main_class(dataset_module.module_path		,	dataset=_lowercase				)

     _UpperCamelCase:  DatasetBuilder    						=			builder_cls(
         cache_dir=_lowercase		,	config_name=_lowercase		,	hash=dataset_module.hash		,	)

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




@pytest.mark.integration
def    lowerCAmelCase_  (		lowercase:				str		)     ->					Any:







 '''simple docstring'''
 _UpperCamelCase:  List[str]    						=			tmp_path_factory.mktemp('''test_hf_gcp'''		) / '''test_wikipedia_simple'''
 _UpperCamelCase:  Optional[int]    						=			dataset_module_factory('''wikipedia'''	,       cache_dir=lowercase		)
 _UpperCamelCase:  Optional[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:  int    						=			None
 builder_instance.download_and_prepare()
 _UpperCamelCase:  Dict    						=			builder_instance.as_dataset()
 assert ds





@pytest.mark.integration
def    lowerCAmelCase_  (		lowercase:				Optional[int]		)     ->					Union[str, Any]:







 '''simple docstring'''
 _UpperCamelCase:  Optional[int]    						=			dataset_module_factory('''wikipedia'''	,       cache_dir=lowercase		)
 _UpperCamelCase:  Any    						=			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:  Any    						=			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''']		)		)
import torch




def    lowerCAmelCase_  (		)     ->					int:







 '''simple docstring'''
 if torch.cuda.is_available():
  _UpperCamelCase:  Any    						=			torch.cuda.device_count()
 else:
  _UpperCamelCase:  Union[str, Any]    						=			0
 print(F"""Successfully ran on {num_gpus} GPUs"""		)


if __name__ == "__main__":
  main()