



'''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_				(       __UpperCAmelCase      ):







						def __init__(	self :   str					,     lowerCAmelCase__ :   int					,     lowerCAmelCase__ :   List[str] = None					,     lowerCAmelCase__ :   str = None					,     lowerCAmelCase__ :   str = None					,     lowerCAmelCase__ :   Optional[Any] = False					,     lowerCAmelCase__ :   List[str] = False					,     lowerCAmelCase__ :   List[Any] = None					,     **lowerCAmelCase__ :   Optional[Any]					,     ):

													"""simple docstring"""
													super().__init__(
													    lowerCAmelCase_					,     split=lowerCAmelCase_					,     features=lowerCAmelCase_					,     cache_dir=lowerCAmelCase_					,     keep_in_memory=lowerCAmelCase_					,     streaming=lowerCAmelCase_					,     num_proc=lowerCAmelCase_					,     **lowerCAmelCase_					,     )
													SCREAMING_SNAKE_CASE       :   str         =      path_or_paths if isinstance(lowerCAmelCase_					,     lowerCAmelCase_					) else {self.split: path_or_paths}
													SCREAMING_SNAKE_CASE       :   List[Any]         =      Text(
													    cache_dir=lowerCAmelCase_					,     data_files=lowerCAmelCase_					,     features=lowerCAmelCase_					,     **lowerCAmelCase_					,     )







						def        __lowercase     (	self :   Tuple					):

													"""simple docstring"""
													# Build iterable dataset
													if self.streaming:
																				SCREAMING_SNAKE_CASE       :   Any         =      self.builder.as_streaming_dataset(split=self.split					)
													# Build regular (map-style) dataset
													else:
																				SCREAMING_SNAKE_CASE       :   int         =      None
																				SCREAMING_SNAKE_CASE       :   List[str]         =      None
																				SCREAMING_SNAKE_CASE       :   List[str]         =      None
																				SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      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       :   str         =      self.builder.as_dataset(
																				    split=self.split					,     verification_mode=lowerCAmelCase_					,     in_memory=self.keep_in_memory					)
													return dataset












"""simple docstring"""
lowerCAmelCase__    						=			'\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

lowerCAmelCase__    						=			[{'type': 'code', 'content': INSTALL_CONTENT}]
lowerCAmelCase__    						=			{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}

