"""simple docstring"""





from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands





def        a_  (   ):





       '''simple docstring'''

       lowercase__    :	List[str]     					=			ArgumentParser('Transformers CLI tool'     ,				usage='transformers-cli <command> [<args>]'  )
       lowercase__    :	int     					=			parser.add_subparsers(help='transformers-cli command helpers'  )

       # Register commands
       ConvertCommand.register_subcommand(_lowerCAmelCase  )
       DownloadCommand.register_subcommand(_lowerCAmelCase  )
       EnvironmentCommand.register_subcommand(_lowerCAmelCase  )
       RunCommand.register_subcommand(_lowerCAmelCase  )
       ServeCommand.register_subcommand(_lowerCAmelCase  )
       UserCommands.register_subcommand(_lowerCAmelCase  )
       AddNewModelCommand.register_subcommand(_lowerCAmelCase  )
       AddNewModelLikeCommand.register_subcommand(_lowerCAmelCase  )
       LfsCommands.register_subcommand(_lowerCAmelCase  )
       PTtoTFCommand.register_subcommand(_lowerCAmelCase  )

       # Let's go
       lowercase__    :	List[Any]     					=			parser.parse_args()

       if not hasattr(_lowerCAmelCase     ,				'func'  ):
              parser.print_help()
              exit(1  )

       # Run
       lowercase__    :	str     					=			args.func(_lowerCAmelCase  )
       service.run()


if __name__ == "__main__":
       main()


"""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     :		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_  (   _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__	:					str										=						None
      lowerCamelCase__	:					Optional[Any]										=						None


      def 	_UpperCAmelCase (     self	,    a	,    a							) ->      List[Any]:
             with TemporaryDirectory() as tmp_dir:
                    lowercase__    :	List[str]     					=			dataset_module_factory(a	,    cache_dir=a							)

                    lowercase__    :	List[Any]     					=			import_main_class(dataset_module.module_path	,    dataset=a							)

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

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





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





       '''simple docstring'''

       lowercase__    :	Union[str, Any]     					=			tmp_path_factory.mktemp('test_hf_gcp'  ) / 'test_wikipedia_simple'
       lowercase__    :	int     					=			dataset_module_factory('wikipedia'     ,				cache_dir=_lowerCAmelCase  )
       lowercase__    :	Optional[int]     					=			import_main_class(dataset_module.module_path  )
       lowercase__    :	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
       lowercase__    :	Optional[int]     					=			None
       builder_instance.download_and_prepare()
       lowercase__    :	Optional[int]     					=			builder_instance.as_dataset()
       assert ds






@pytest.mark.integration
def        a_  (   _lowerCAmelCase						:				Optional[Any]  ):





       '''simple docstring'''

       lowercase__    :	Optional[int]     					=			dataset_module_factory('wikipedia'     ,				cache_dir=_lowerCAmelCase  )
       lowercase__    :	List[str]     					=			import_main_class(dataset_module.module_path     ,				dataset=_lowerCAmelCase  )
       lowercase__    :	DatasetBuilder     					=			builder_cls(
           cache_dir=_lowerCAmelCase     ,				config_name='20220301.frr'     ,				hash=dataset_module.hash     ,				)
       lowercase__    :	Union[str, Any]     					=			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']  )  )

