



"""simple docstring"""






import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class   a__			(       UpperCamelCase_  ):
						snake_case__             = ["image_processor", "tokenizer"]
						snake_case__             = "ViTImageProcessor"
						snake_case__             = ("CLIPTokenizer", "CLIPTokenizerFast")





						def __init__(							self      :	List[str]     ,a__      :	List[Any]=None     ,a__      :	List[str]=None     ,**a__      :	Optional[int])						->       List[Any]:




											"""simple docstring"""







											_lowerCAmelCase:str									=  None
											if "feature_extractor" in kwargs:
																warnings.warn(
																    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
																    ''' instead.'''     ,a__     ,)
																_lowerCAmelCase:Union[str, Any]									=  kwargs.pop('''feature_extractor''')

											_lowerCAmelCase:Tuple									=  image_processor if image_processor is not None else feature_extractor
											if image_processor is None:
																raise ValueError('''You need to specify an `image_processor`.''')
											if tokenizer is None:
																raise ValueError('''You need to specify a `tokenizer`.''')

											super().__init__(a__     ,a__)





						def __call__(							self      :	str     ,a__      :	Optional[Any]=None     ,a__      :	Optional[Any]=None     ,a__      :	Dict=None     ,a__      :	str=None     ,**a__      :	List[str])						->       List[Any]:




											"""simple docstring"""







											if text is None and visual_prompt is None and images is None:
																raise ValueError('''You have to specify either text, visual prompt or images.''')

											if text is not None and visual_prompt is not None:
																raise ValueError('''You have to specify exactly one type of prompt. Either text or visual prompt.''')

											if text is not None:
																_lowerCAmelCase:Any									=  self.tokenizer(a__     ,return_tensors=a__     ,**a__)

											if visual_prompt is not None:
																_lowerCAmelCase:Optional[int]									=  self.image_processor(a__     ,return_tensors=a__     ,**a__)

											if images is not None:
																_lowerCAmelCase:Optional[int]									=  self.image_processor(a__     ,return_tensors=a__     ,**a__)

											if visual_prompt is not None and images is not None:
																_lowerCAmelCase:int									=  {
																    '''pixel_values''': image_features.pixel_values,
																    '''conditional_pixel_values''': prompt_features.pixel_values,
																}
																return encoding
											elif text is not None and images is not None:
																_lowerCAmelCase:Union[str, Any]									=  image_features.pixel_values
																return encoding
											elif text is not None:
																return encoding
											elif visual_prompt is not None:
																_lowerCAmelCase:Tuple									=  {
																    '''conditional_pixel_values''': prompt_features.pixel_values,
																}
																return encoding
											else:
																return BatchEncoding(data=dict(**a__)     ,tensor_type=a__)





						def       __UpperCamelCase     (							self      :	List[str]     ,*a__      :	str     ,**a__      :	Optional[int])						->       Union[str, Any]:




											"""simple docstring"""







											return self.tokenizer.batch_decode(*a__     ,**a__)





						def       __UpperCamelCase     (							self      :	Dict     ,*a__      :	Tuple     ,**a__      :	List[str])						->       Optional[Any]:




											"""simple docstring"""







											return self.tokenizer.decode(*a__     ,**a__)





						@property
						def       __UpperCamelCase     (							self      :	List[Any])						->       Optional[Any]:




											"""simple docstring"""







											warnings.warn(
											    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''     ,a__     ,)
											return self.image_processor_class







						@property
						def       __UpperCamelCase     (							self      :	Any)						->       List[Any]:




											"""simple docstring"""







											warnings.warn(
											    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''     ,a__     ,)
											return self.image_processor












"""simple docstring"""






# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    '''stable diffusion controlnet''',
    '''0.22.0''',
    '''Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.''',
    standard_warn=False,
    stacklevel=3,
)






