






'''simple docstring'''

def    lowercase__			(				__UpperCamelCase		,						__UpperCamelCase   )->			list:
      UpperCamelCase      = word.split()

      def justify(__UpperCamelCase		,						__UpperCamelCase		,						__UpperCamelCase   ) -> str:
            UpperCamelCase      = max_width - width
            UpperCamelCase      = len(__UpperCamelCase   )
            if len(__UpperCamelCase   ) == 1:
                  # if there is only word in line
                  # just insert overall_spaces_count for the remainder of line
                  return line[0] + " " * overall_spaces_count
            else:
                  UpperCamelCase      = words_count - 1
                  # num_spaces_between_words_list[i] : tells you to insert
                  # num_spaces_between_words_list[i] spaces
                  # after word on line[i]
                  UpperCamelCase      = spaces_to_insert_between_words * [
                      overall_spaces_count // spaces_to_insert_between_words
                  ]
                  UpperCamelCase      = (
                      overall_spaces_count % spaces_to_insert_between_words
                  )
                  # distribute spaces via round robin to the left words
                  for i in range(__UpperCamelCase   ):
                        num_spaces_between_words_list[i] += 1
                  UpperCamelCase      = []
                  for i in range(__UpperCamelCase   ):
                        # add the word
                        aligned_words_list.append(line[i]   )
                        # add the spaces to insert
                        aligned_words_list.append(num_spaces_between_words_list[i] * """ """   )
                  # just add the last word to the sentence
                  aligned_words_list.append(line[-1]   )
                  # join the aligned words list to form a justified line
                  return "".join(__UpperCamelCase   )

      UpperCamelCase      = []
      UpperCamelCase      = []
      UpperCamelCase      = 0
      for word in words:
            if width + len(__UpperCamelCase   ) + len(__UpperCamelCase   ) <= max_width:
                  # keep adding words until we can fill out max_width
                  # width = sum of length of all words (without overall_spaces_count)
                  # len(word) = length of current word
                  # len(line) = number of overall_spaces_count to insert between words
                  line.append(__UpperCamelCase   )
                  width += len(__UpperCamelCase   )
            else:
                  # justify the line and add it to result
                  answer.append(justify(__UpperCamelCase		,						__UpperCamelCase		,						__UpperCamelCase   )   )
                  # reset new line and new width
                  UpperCamelCase  ,UpperCamelCase      = [word], len(__UpperCamelCase   )
      UpperCamelCase      = max_width - width - len(__UpperCamelCase   )
      answer.append(""" """.join(__UpperCamelCase   ) + (remaining_spaces + 1) * """ """   )
      return answer


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     a_						(      lowerCamelCase    ):
  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      ,		*_SCREAMING_SNAKE_CASE      ,		**_SCREAMING_SNAKE_CASE				)  ->				Any:



        """simple docstring"""






        requires_backends(self      ,		["""vision"""]				)
        super().__init__(*_SCREAMING_SNAKE_CASE      ,		**_SCREAMING_SNAKE_CASE				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				str:



        """simple docstring"""






        return self.pre_processor(images=_SCREAMING_SNAKE_CASE      ,		return_tensors="""pt"""				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				str:



        """simple docstring"""






        return self.model.generate(**_SCREAMING_SNAKE_CASE				)


  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				Union[str, Any]:



        """simple docstring"""






        return self.pre_processor.batch_decode(_SCREAMING_SNAKE_CASE      ,		skip_special_tokens=_SCREAMING_SNAKE_CASE				)[0].strip()
