






from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class       _UpperCAmelCase					(       A__	):

				"""simple docstring"""




				def __init__(     self						:    Dict,  lowerCamelCase						:    pyspark.sql.DataFrame,  lowerCamelCase						:    Optional[NamedSplit] = None,  lowerCamelCase						:    Optional[Features] = None,  lowerCamelCase						:    bool = True,  lowerCamelCase						:    str = None,  lowerCamelCase						:    bool = False,  lowerCamelCase						:    str = None,  lowerCamelCase						:    bool = True,  lowerCamelCase						:    str = "arrow",  **lowerCamelCase						:    str,  ):

								'''simple docstring'''
								super().__init__(
								    split=lowerCamelCase,  features=lowerCamelCase,  cache_dir=lowerCamelCase,  keep_in_memory=lowerCamelCase,  streaming=lowerCamelCase,  **lowerCamelCase,  )
								lowercase__    =			load_from_cache_file
								lowercase__    =			file_format
								lowercase__    =			Spark(
								    df=lowerCamelCase,  features=lowerCamelCase,  cache_dir=lowerCamelCase,  working_dir=lowerCamelCase,  **lowerCamelCase,  )




				def 				lowercase__   (     self						:    List[Any]  ):

								'''simple docstring'''
								if self.streaming:
												return self.builder.as_streaming_dataset(split=self.split  )
								lowercase__    =			None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
								self.builder.download_and_prepare(
								    download_mode=lowerCamelCase,  file_format=self._file_format,  )
								return self.builder.as_dataset(split=self.split  )












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A__	:			Optional[int]			   = {}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__	:			Optional[int]			   = ['GPTSw3Tokenizer']


if TYPE_CHECKING:
							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_gpt_swa import GPTSwaTokenizer

else:
							import sys

							A__	:			Optional[int]			   = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




