
"""simple docstring"""
from __future__ import annotations

from collections.abc import MutableSequence
class 			UpperCamelCase      :
     def __init__(     self  ,     snake_case__  ,     snake_case__				):




       """simple docstring"""


       if len(snake_case__				) != degree + 1:
         raise ValueError(
             "The number of coefficients should be equal to the degree + 1."				)

       _SCREAMING_SNAKE_CASE   :				list[float]							    = list(snake_case__				)
       _SCREAMING_SNAKE_CASE   :				int							    = degree
     def __add__(     self  ,     snake_case__				):




       """simple docstring"""


       if self.degree > polynomial_a.degree:
         _SCREAMING_SNAKE_CASE   :				Dict							    = self.coefficients[:]
         for i in range(polynomial_a.degree + 1				):
           coefficients[i] += polynomial_a.coefficients[i]
         return Polynomial(self.degree  ,     snake_case__				)
       else:
         _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = polynomial_a.coefficients[:]
         for i in range(self.degree + 1				):
           coefficients[i] += self.coefficients[i]
         return Polynomial(polynomial_a.degree  ,     snake_case__				)
     def __sub__(     self  ,     snake_case__				):




       """simple docstring"""


       return self + polynomial_a * Polynomial(0  ,     [-1]				)
     def __neg__(     self				):




       """simple docstring"""


       return Polynomial(self.degree  ,     [-c for c in self.coefficients]				)
     def __mul__(     self  ,     snake_case__				):




       """simple docstring"""


       _SCREAMING_SNAKE_CASE   :				list[float]							    = [0] * (self.degree + polynomial_a.degree + 1)
       for i in range(self.degree + 1				):
         for j in range(polynomial_a.degree + 1				):
           coefficients[i + j] += (
               self.coefficients[i] * polynomial_a.coefficients[j]
           )

       return Polynomial(self.degree + polynomial_a.degree  ,     snake_case__				)
     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__				):




       """simple docstring"""


       _SCREAMING_SNAKE_CASE   :				int | float							    = 0
       for i in range(self.degree + 1				):
         result += self.coefficients[i] * (substitution**i)
       return result
     def __str__(     self				):




       """simple docstring"""


       _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = ""
       for i in range(self.degree  ,     -1  ,     -1				):
         if self.coefficients[i] == 0:
           continue
         elif self.coefficients[i] > 0:
           if polynomial:
             polynomial += " + "
         else:
           polynomial += " - "

         if i == 0:
           polynomial += str(abs(self.coefficients[i]				)				)
         elif i == 1:
           polynomial += str(abs(self.coefficients[i]				)				) + "x"
         else:
           polynomial += str(abs(self.coefficients[i]				)				) + "x^" + str(snake_case__				)

       return polynomial
     def __repr__(     self				):




       """simple docstring"""


       return self.__str__()
     def 				__SCREAMING_SNAKE_CASE							(     self				):




       """simple docstring"""


       _SCREAMING_SNAKE_CASE   :				list[float]							    = [0] * self.degree
       for i in range(self.degree				):
         _SCREAMING_SNAKE_CASE   :				Tuple							    = self.coefficients[i + 1] * (i + 1)
       return Polynomial(self.degree - 1  ,     snake_case__				)
     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__ = 0				):




       """simple docstring"""


       _SCREAMING_SNAKE_CASE   :				list[float]							    = [0] * (self.degree + 2)
       _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = constant
       for i in range(self.degree + 1				):
         _SCREAMING_SNAKE_CASE   :				Dict							    = self.coefficients[i] / (i + 1)
       return Polynomial(self.degree + 1  ,     snake_case__				)
     def __eq__(     self  ,     snake_case__				):




       """simple docstring"""


       if not isinstance(snake_case__  ,     snake_case__				):
         return False

       if self.degree != polynomial_a.degree:
         return False

       for i in range(self.degree + 1				):
         if self.coefficients[i] != polynomial_a.coefficients[i]:
           return False

       return True




     def __ne__(     self  ,     snake_case__				):




       """simple docstring"""


       return not self.__eq__(snake_case__				)





"""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      (							__SCREAMING_SNAKE_CASE  ):
     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  ,     *snake_case__  ,     **snake_case__				):




       """simple docstring"""


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

       super().__init__(*snake_case__  ,     **snake_case__				)
     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__  ,     snake_case__				):




       """simple docstring"""


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

       return {"decoder_input_ids": decoder_input_ids, "pixel_values": pixel_values}
     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__				):




       """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=snake_case__  ,     pad_token_id=self.pre_processor.tokenizer.pad_token_id  ,     eos_token_id=self.pre_processor.tokenizer.eos_token_id  ,     use_cache=snake_case__  ,     num_beams=1  ,     bad_words_ids=[[self.pre_processor.tokenizer.unk_token_id]]  ,     return_dict_in_generate=snake_case__  ,     ).sequences




     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__				):




       """simple docstring"""


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

       return sequence["answer"]



