"""simple docstring"""






from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader

class lowerCamelCase		(_SCREAMING_SNAKE_CASE      ):






					'''simple docstring'''


					def __init__(						self			:				Optional[int]   , _snake_case			:				str   , _snake_case			:				Tuple = None   , _snake_case			:				str = None   , _snake_case			:				Union[str, Any] = None   , _snake_case			:				Tuple = False   , _snake_case			:				Optional[int] = False   , _snake_case			:				List[str] = None   , **_snake_case			:				Any   , )							->       List[Any]:
									super().__init__(
									    __lowerCAmelCase   , split=__lowerCAmelCase   , features=__lowerCAmelCase   , cache_dir=__lowerCAmelCase   , keep_in_memory=__lowerCAmelCase   , streaming=__lowerCAmelCase   , num_proc=__lowerCAmelCase   , **__lowerCAmelCase   , )
									SCREAMING_SNAKE_CASE__		  =				path_or_paths if isinstance(__lowerCAmelCase   , __lowerCAmelCase		) else {self.split: path_or_paths}
									SCREAMING_SNAKE_CASE__		  =				Text(
									    cache_dir=__lowerCAmelCase   , data_files=__lowerCAmelCase   , features=__lowerCAmelCase   , **__lowerCAmelCase   , )



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       int:







									if self.streaming:
													SCREAMING_SNAKE_CASE__		  =				self.builder.as_streaming_dataset(split=self.split		)
									# Build regular (map-style) dataset
									else:
													SCREAMING_SNAKE_CASE__		  =				None
													SCREAMING_SNAKE_CASE__		  =				None
													SCREAMING_SNAKE_CASE__		  =				None
													SCREAMING_SNAKE_CASE__		  =				None

													self.builder.download_and_prepare(
													    download_config=__lowerCAmelCase   , download_mode=__lowerCAmelCase   , verification_mode=__lowerCAmelCase   , base_path=__lowerCAmelCase   , num_proc=self.num_proc   , )
													SCREAMING_SNAKE_CASE__		  =				self.builder.as_dataset(
													    split=self.split   , verification_mode=__lowerCAmelCase   , in_memory=self.keep_in_memory		)
									return dataset





"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import _LazyModule


_A   					=    {'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}


if TYPE_CHECKING:
						from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
						import sys

						_A   					=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




