

from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate


@dataclass(frozen=__snake_case					)
class 				SCREAMING_SNAKE_CASE__ (__snake_case					):
    # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
    __lowerCamelCase						:	str														=					field(default="""summarization"""		,	metadata={"""include_in_asdict_even_if_is_default""": True}					)
    __lowerCamelCase						:	ClassVar[Features]														=					Features({"""text""": Value("""string"""					)}					)
    __lowerCamelCase						:	ClassVar[Features]														=					Features({"""summary""": Value("""string"""					)}					)
    __lowerCamelCase						:	str														=					"text"
    __lowerCamelCase						:	str														=					"summary"





    @property
    def 				snake_case_    (				self):
         return {self.text_column: "text", self.summary_column: "summary"}




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 				SCREAMING_SNAKE_CASE__ (__snake_case					):





    def __init__(				self						,       a						,       a = None						,       a = None						,       a = True						,       a = None						,       a = False						,       a = None						,       a = True						,       a = "arrow"						,       **a						,       ):
         super().__init__(
             split=a						,       features=a						,       cache_dir=a						,       keep_in_memory=a						,       streaming=a						,       **a						,       )
         lowercase__   :       Optional[int]				=	load_from_cache_file
         lowercase__   :       Optional[int]				=	file_format
         lowercase__   :       int				=	Spark(
             df=a						,       features=a						,       cache_dir=a						,       working_dir=a						,       **a						,       )





    def 				snake_case_    (				self):
         if self.streaming:
              return self.builder.as_streaming_dataset(split=self.split)
         lowercase__   :       Dict				=	None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
         self.builder.download_and_prepare(
             download_mode=a						,       file_format=self._file_format						,       )
         return self.builder.as_dataset(split=self.split)

