
from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike




class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	def __init__(					self		:str     ,   a		:Optional[NestedDataStructureLike[PathLike]] = None     ,   a		:Optional[NamedSplit] = None     ,   a		:Optional[Features] = None     ,   a		:str = None     ,   a		:bool = False     ,   a		:bool = False     ,   a		:Optional[int] = None     ,   **a		:List[Any]     ,   )		-> str:
								__UpperCamelCase	:   List[str]			   =					path_or_paths
								__UpperCamelCase	:   List[str]			   =					split if split or isinstance(a     ,   a						) else "train"
								__UpperCamelCase	:   Union[str, Any]			   =					features
								__UpperCamelCase	:   Any			   =					cache_dir
								__UpperCamelCase	:   Optional[int]			   =					keep_in_memory
								__UpperCamelCase	:   Union[str, Any]			   =					streaming
								__UpperCamelCase	:   Optional[Any]			   =					num_proc
								__UpperCamelCase	:   Tuple			   =					kwargs







	@abstractmethod
	def    _lowerCamelCase				(					self		:int						)		-> Union[Dataset, DatasetDict, IterableDataset, IterableDatasetDict]:
								pass




class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	def __init__(					self		:List[Any]     ,   a		:Optional[Features] = None     ,   a		:str = None     ,   a		:bool = False     ,   a		:bool = False     ,   a		:Optional[int] = None     ,   **a		:List[str]     ,   )		-> Union[str, Any]:
								__UpperCamelCase	:   str			   =					features
								__UpperCamelCase	:   str			   =					cache_dir
								__UpperCamelCase	:   Optional[Any]			   =					keep_in_memory
								__UpperCamelCase	:   Optional[Any]			   =					streaming
								__UpperCamelCase	:   Tuple			   =					num_proc
								__UpperCamelCase	:   int			   =					kwargs







	@abstractmethod
	def    _lowerCamelCase				(					self		:int						)		-> Union[Dataset, IterableDataset]:
								pass

import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
		lowercase  :					int													=       {
		    'linear': PIL.Image.Resampling.BILINEAR,
		    'bilinear': PIL.Image.Resampling.BILINEAR,
		    'bicubic': PIL.Image.Resampling.BICUBIC,
		    'lanczos': PIL.Image.Resampling.LANCZOS,
		    'nearest': PIL.Image.Resampling.NEAREST,
		}
else:
		lowercase  :					Any													=       {
		    'linear': PIL.Image.LINEAR,
		    'bilinear': PIL.Image.BILINEAR,
		    'bicubic': PIL.Image.BICUBIC,
		    'lanczos': PIL.Image.LANCZOS,
		    'nearest': PIL.Image.NEAREST,
		}




def 	_SCREAMING_SNAKE_CASE					(		_lowerCamelCase :			int)					->    Any:






							'''simple docstring'''





							__UpperCamelCase	:   Union[str, Any]			   =					(images / 2 + 0.5).clamp(0						,  1)
							__UpperCamelCase	:   int			   =					images.cpu().permute(0						,  2						,  3						,  1).float().numpy()
							__UpperCamelCase	:   Dict			   =					numpy_to_pil(_lowerCamelCase)
							return images




def 	_SCREAMING_SNAKE_CASE					(		_lowerCamelCase :			Optional[Any])					->    Optional[Any]:






							'''simple docstring'''





							if images.ndim == 3:
														__UpperCamelCase	:   Optional[int]			   =					images[None, ...]
							__UpperCamelCase	:   Dict			   =					(images * 255).round().astype("uint8")
							if images.shape[-1] == 1:
														# special case for grayscale (single channel) images
														__UpperCamelCase	:   int			   =					[Image.fromarray(image.squeeze()						,  mode="L") for image in images]
							else:
														__UpperCamelCase	:   Union[str, Any]			   =					[Image.fromarray(_lowerCamelCase) for image in images]

							return pil_images