


def     lowerCamelCase( a__):
				if not all(char in '''01''' for char in bin_string):
								raise ValueError('''Non-binary value was passed to the function''')
				if not bin_string:
								raise ValueError('''Empty string was passed to the function''')
				_SCREAMING_SNAKE_CASE      	=''''''
				while len(A_) % 3 != 0:
								_SCREAMING_SNAKE_CASE      	='''0''' + bin_string
				_SCREAMING_SNAKE_CASE      	=[
				    bin_string[index : index + 3]
				    for index in range(len(A_))
				    if index % 3 == 0
				]
				for bin_group in bin_string_in_3_list:
								_SCREAMING_SNAKE_CASE      	=0
								for index, val in enumerate(A_):
												oct_val += int(2 ** (2 - index) * int(A_))
								oct_string += str(A_)
				return oct_string


if __name__ == "__main__":
							from doctest import testmod

							testmod()


"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					lowercase__												=			"Salesforce/blip-image-captioning-base"
					lowercase__												=			(
					    "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."
					)
					lowercase__												=			"image_captioner"
					lowercase__												=			AutoModelForVisionaSeq

					lowercase__												=			["image"]
					lowercase__												=			["text"]







					def __init__(			self     :							int  ,*lowercase_     :							int  ,**lowercase_     :							List[str]						):
						requires_backends(self  ,['''vision''']						)
						super().__init__(*lowercase_  ,**lowercase_						)







					def 			__lowerCAmelCase					(			self     :							List[str]  ,lowercase_     :							"Image"						):
						return self.pre_processor(images=lowercase_  ,return_tensors='''pt'''						)







					def 			__lowerCAmelCase					(			self     :							List[Any]  ,lowercase_     :							Any						):
						return self.model.generate(**lowercase_						)







					def 			__lowerCAmelCase					(			self     :							Dict  ,lowercase_     :							Union[str, Any]						):
						return self.pre_processor.batch_decode(lowercase_  ,skip_special_tokens=lowercase_						)[0].strip()




