
'''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.
import re

from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool


if is_vision_available():
    from PIL import Image


class  _UpperCAmelCase ( lowerCAmelCase__    ):

     """simple docstring"""

     a_    	=					'''naver-clova-ix/donut-base-finetuned-docvqa'''
     a_    	=					(
         '''This is a tool that answers a question about an document (pdf). It takes an input named `document` which '''
         '''should be the document containing the information, as well as a `question` that is the question about the '''
         '''document. It returns a text that contains the answer to the question.'''
     )
     a_    	=					'''document_qa'''
     a_    	=					AutoProcessor
     a_    	=					VisionEncoderDecoderModel

     a_    	=					['''image''', '''text''']
     a_    	=					['''text''']


     def __init__(      self							,		*lowerCAmelCase_							,		**lowerCAmelCase_ ):

           '''simple docstring'''

           if not is_vision_available():
                 raise ValueError("""Pillow must be installed to use the DocumentQuestionAnsweringTool.""" )

           super().__init__(*A__							,		**A__ )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_ ):

           '''simple docstring'''

           a_      :	Optional[int]      =							"""<s_docvqa><s_question>{user_input}</s_question><s_answer>"""
           a_      :	List[str]      =							task_prompt.replace("""{user_input}"""							,		A__ )
           a_      :	Optional[Any]      =							self.pre_processor.tokenizer(
               A__							,		add_special_tokens=A__							,		return_tensors="""pt""" ).input_ids
           a_      :	int      =							self.pre_processor(A__							,		return_tensors="""pt""" ).pixel_values

           return {"decoder_input_ids": decoder_input_ids, "pixel_values": pixel_values}


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

           '''simple docstring'''

           return self.model.generate(
               inputs["""pixel_values"""].to(self.device )							,		decoder_input_ids=inputs["""decoder_input_ids"""].to(self.device )							,		max_length=self.model.decoder.config.max_position_embeddings							,		early_stopping=A__							,		pad_token_id=self.pre_processor.tokenizer.pad_token_id							,		eos_token_id=self.pre_processor.tokenizer.eos_token_id							,		use_cache=A__							,		num_beams=1							,		bad_words_ids=[[self.pre_processor.tokenizer.unk_token_id]]							,		return_dict_in_generate=A__							,		).sequences






     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

           '''simple docstring'''

           a_      :	Optional[int]      =							self.pre_processor.batch_decode(A__ )[0]
           a_      :	Optional[Any]      =							sequence.replace(self.pre_processor.tokenizer.eos_token							,		"""""" )
           a_      :	Optional[int]      =							sequence.replace(self.pre_processor.tokenizer.pad_token							,		"""""" )
           a_      :	List[Any]      =							re.sub(R"""<.*?>"""							,		""""""							,		A__							,		count=1 ).strip()  # remove first task start token
           a_      :	Tuple      =							self.pre_processor.tokenajson(A__ )

           return sequence["answer"]




'''simple docstring'''

def 	_snake_case						(      A_       :    list   ):
  """simple docstring"""







  if len(A_   ) <= 1:
    return lst

  a_      :	Any      =							1

  while i < len(A_   ):
    if lst[i - 1] <= lst[i]:
      i += 1
    else:
      a_      , a_      :	int      =							lst[i], lst[i - 1]
      i -= 1
      if i == 0:
        a_      :	List[str]      =							1

  return lst


if __name__ == "__main__":
    __snake_case:  List[Any]								=			input("Enter numbers separated by a comma:\n").strip()
    __snake_case:  Optional[int]								=			[int(item) for item in user_input.split(",")]
    print(gnome_sort(unsorted))


