






"""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        a     (   a_	):
    UpperCAmelCase_ :     List[Any]	     ="Salesforce/blip-image-captioning-base"
    UpperCAmelCase_ :     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_ :     Optional[int]	     ="image_captioner"
    UpperCAmelCase_ :     List[Any]	     =AutoModelForVisionaSeq

    UpperCAmelCase_ :     List[str]	     =["image"]
    UpperCAmelCase_ :     Optional[int]	     =["text"]







    def __init__(			self							,		*_lowerCamelCase							,		**_lowerCamelCase       ):
      requires_backends(self							,		['vision']       )
      super().__init__(*_lowerCamelCase							,		**_lowerCamelCase       )







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      return self.pre_processor(images=_lowerCamelCase							,		return_tensors='pt'       )







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      return self.model.generate(**_lowerCamelCase       )







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      return self.pre_processor.batch_decode(_lowerCamelCase							,		skip_special_tokens=_lowerCamelCase       )[0].strip()










"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  int = 1_00    ):





  '''simple docstring'''





  lowercase							    =       0
  lowercase							    =       0
  for i in range(1		,					n + 1    ):
    sum_of_squares += i**2
    sum_of_ints += i
  return sum_of_ints**2 - sum_of_squares


if __name__ == "__main__":
    print(F'''{solution() = }''')


