
'''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   (   __snake_case				):







							'''simple docstring'''

							def __init__(self  ,  UpperCAmelCase  ,  UpperCAmelCase = None  ,  UpperCAmelCase = None  ,  UpperCAmelCase = None  ,  UpperCAmelCase = False  ,  UpperCAmelCase = False  ,  UpperCAmelCase = None  ,  **UpperCAmelCase  ,  )					->       str:
														super().__init__(
														    UpperCAmelCase  ,  split=UpperCAmelCase  ,  features=UpperCAmelCase  ,  cache_dir=UpperCAmelCase  ,  keep_in_memory=UpperCAmelCase  ,  streaming=UpperCAmelCase  ,  num_proc=UpperCAmelCase  ,  **UpperCAmelCase  ,  )
														_snake_case       =  path_or_paths if isinstance(UpperCAmelCase  ,  UpperCAmelCase  ) else {self.split: path_or_paths}
														_snake_case       =  Text(
														    cache_dir=UpperCAmelCase  ,  data_files=UpperCAmelCase  ,  features=UpperCAmelCase  ,  **UpperCAmelCase  ,  )





							def 	lowercase							(self  )					->       Dict:
														# Build iterable dataset
														if self.streaming:
																					_snake_case       =  self.builder.as_streaming_dataset(split=self.split  )
														# Build regular (map-style) dataset
														else:
																					_snake_case       =  None
																					_snake_case       =  None
																					_snake_case       =  None
																					_snake_case       =  None

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

'''simple docstring'''
import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionInpaintPipeline` instead.'
)