


from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
						from PIL import Image







class 	snake_case_       (SCREAMING_SNAKE_CASE__				):
					UpperCAmelCase__ :   str   				=      '''Salesforce/blip-image-captioning-base'''
					UpperCAmelCase__ :   List[str]   				=      (
					    '''This is a tool that generates a description of an image. It takes an input named `image` which should be the '''
					    '''image to caption, and returns a text that contains the description in English.'''
					)
					UpperCAmelCase__ :   Union[str, Any]   				=      '''image_captioner'''
					UpperCAmelCase__ :   List[Any]   				=      AutoModelForVisionaSeq

					UpperCAmelCase__ :   Tuple   				=      ['''image''']
					UpperCAmelCase__ :   List[str]   				=      ['''text''']
					def __init__(				self       :Tuple      ,*__snake_case       :str      ,**__snake_case       :int				) ->   int:
												requires_backends(self      ,['vision']				)
												super().__init__(*__snake_case      ,**__snake_case				)
					def 			lowerCamelCase__(				self       :int      ,__snake_case       :"Image"				) ->   str:
												return self.pre_processor(images=__snake_case      ,return_tensors='pt'				)
					def 			lowerCamelCase__(				self       :Dict      ,__snake_case       :List[Any]				) ->   Union[str, Any]:
												return self.model.generate(**__snake_case				)



					def 			lowerCamelCase__(				self       :Optional[Any]      ,__snake_case       :Dict				) ->   int:
												return self.pre_processor.batch_decode(__snake_case      ,skip_special_tokens=__snake_case				)[0].strip()








from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *




