





from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available


@dataclass
class 			lowercase				(							a_     ):



						"""simple docstring"""

						_UpperCamelCase  :	Union[List[PIL.Image.Image], np.ndarray]
						_UpperCamelCase  :	Optional[List[bool]]


if is_transformers_available() and is_torch_available():
		from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline













import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowercase_		:				str				=						logging.get_logger(__name__)


class 			lowercase				(							a_     ):



						"""simple docstring"""

						def __init__(    self			:		int ,				*lowerCamelCase_			:		str ,				**lowerCamelCase_			:		Tuple					):





										'''simple docstring'''







										warnings.warn(
										    'The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
										    ' Please use SegformerImageProcessor instead.' ,				lowerCamelCase_ ,				)
										super().__init__(*lowerCamelCase_ ,				**lowerCamelCase_					)






