

import warnings

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

class     a__  (    __lowercase	):
			"""simple docstring"""







			__lowerCamelCase       				=				["""image_processor""", """tokenizer"""]
			__lowerCamelCase       				=				"""ViTImageProcessor"""
			__lowerCamelCase       				=				("""CLIPTokenizer""", """CLIPTokenizerFast""")


			def __init__(			self					,					lowercase=None					,					lowercase=None					,					**lowercase				)     ->  List[str]:
							'''simple docstring'''






							A__						=	None
							if "feature_extractor" in kwargs:
											warnings.warn(
											    "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
											    " instead."					,					SCREAMING_SNAKE_CASE__					,					)
											A__						=	kwargs.pop("feature_extractor"				)

							A__						=	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__(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				)


			def __call__(			self					,					lowercase=None					,					lowercase=None					,					lowercase=None					,					lowercase=None					,					**lowercase				)     ->  Optional[int]:
							'''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:
											A__						=	self.tokenizer(SCREAMING_SNAKE_CASE__					,					return_tensors=SCREAMING_SNAKE_CASE__					,					**SCREAMING_SNAKE_CASE__				)

							if visual_prompt is not None:
											A__						=	self.image_processor(SCREAMING_SNAKE_CASE__					,					return_tensors=SCREAMING_SNAKE_CASE__					,					**SCREAMING_SNAKE_CASE__				)

							if images is not None:
											A__						=	self.image_processor(SCREAMING_SNAKE_CASE__					,					return_tensors=SCREAMING_SNAKE_CASE__					,					**SCREAMING_SNAKE_CASE__				)

							if visual_prompt is not None and images is not None:
											A__						=	{
											    "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:
											A__						=	image_features.pixel_values
											return encoding
							elif text is not None:
											return encoding
							elif visual_prompt is not None:
											A__						=	{
											    "conditional_pixel_values": prompt_features.pixel_values,
											}
											return encoding
							else:
											return BatchEncoding(data=dict(**SCREAMING_SNAKE_CASE__				)					,					tensor_type=SCREAMING_SNAKE_CASE__				)


			def    UpperCamelCase						(			self					,					*lowercase					,					**lowercase				)     ->  List[str]:
							'''simple docstring'''






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


			def    UpperCamelCase						(			self					,					*lowercase					,					**lowercase				)     ->  Any:
							'''simple docstring'''






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


			@property
			def    UpperCamelCase						(			self				)     ->  List[Any]:
							'''simple docstring'''






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


			@property
			def    UpperCamelCase						(			self				)     ->  Any:
							'''simple docstring'''






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



from abc import ABC, abstractmethod
from argparse import ArgumentParser

class    lowerCAmelCase__     (	__lowercase			):






		@staticmethod
		@abstractmethod
		def  __A       (		SCREAMING_SNAKE_CASE__		:							ArgumentParser  )     ->							str:
						raise NotImplementedError()







		@abstractmethod
		def  __A       (		self		:							Optional[int]  )     ->							Union[str, Any]:
						raise NotImplementedError()



