




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 		_A   (    a__ ):
  _UpperCamelCase  :     Optional[int]					=     '''naver-clova-ix/donut-base-finetuned-docvqa'''
  _UpperCamelCase  :     Tuple					=     (
      '''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.'''
  )
  _UpperCamelCase  :     Any					=     '''document_qa'''
  _UpperCamelCase  :     Tuple					=     AutoProcessor
  _UpperCamelCase  :     List[Any]					=     VisionEncoderDecoderModel

  _UpperCamelCase  :     List[Any]					=     ['''image''', '''text''']
  _UpperCamelCase  :     List[Any]					=     ['''text''']






  def __init__(    self						:      Any ,		*_A						:      List[str] ,		**_A						:      int )						->       Tuple:






       """simple docstring"""







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

       super().__init__(*_UpperCAmelCase ,		**_UpperCAmelCase )






  def    __a     (    self						:      str ,		_A						:      List[str] ,		_A						:      Dict )						->       int:






       """simple docstring"""







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

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






  def    __a     (    self						:      Optional[int] ,		_A						:      Union[str, Any] )						->       List[str]:






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






  def    __a     (    self						:      int ,		_A						:      int )						->       Optional[Any]:






       """simple docstring"""







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

       return sequence["answer"]






'''simple docstring'''




import mpmath  # for roots of unity
import numpy as np


class 					SCREAMING_SNAKE_CASE       :


     def __init__(		self		,      _UpperCAmelCase=None		,      _UpperCAmelCase=None):

          '''simple docstring'''






          __A		:					List[Any]						=			list(poly_a or [0])[:]
          __A		:					Optional[int]						=			list(poly_b or [0])[:]

          # Remove leading zero coefficients
          while self.polyA[-1] == 0:
               self.polyA.pop()
          __A		:					Union[str, Any]						=			len(self.polyA)

          while self.polyB[-1] == 0:
               self.polyB.pop()
          __A		:					Optional[int]						=			len(self.polyB)

          # Add 0 to make lengths equal a power of 2
          __A		:					Optional[Any]						=			int(
              2 ** np.ceil(np.loga(len(self.polyA) + len(self.polyB) - 1)))

          while len(self.polyA) < self.c_max_length:
               self.polyA.append(0)
          while len(self.polyB) < self.c_max_length:
               self.polyB.append(0)
          # A complex root used for the fourier transform
          __A		:					str						=			complex(mpmath.root(x=1		,      n=self.c_max_length		,      k=1))

          # The product
          __A		:					Tuple						=			self.__multiply()


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






          __A		:					Optional[int]						=			[[x] for x in self.polyA] if which == 'A' else [[x] for x in self.polyB]
          # Corner case
          if len(_UpperCAmelCase) <= 1:
               return dft[0]
          #
          __A		:					Dict						=			self.c_max_length // 2
          while next_ncol > 0:
               __A		:					Optional[Any]						=			[[] for i in range(_UpperCAmelCase)]
               __A		:					Tuple						=			self.root**next_ncol

               # First half of next step
               __A		:					Optional[Any]						=			1
               for j in range(self.c_max_length // (next_ncol * 2)):
                    for i in range(_UpperCAmelCase):
                         new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j])
                    current_root *= root
               # Second half of next step
               __A		:					List[str]						=			1
               for j in range(self.c_max_length // (next_ncol * 2)):
                    for i in range(_UpperCAmelCase):
                         new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j])
                    current_root *= root
               # Update
               __A		:					Optional[int]						=			new_dft
               __A		:					Tuple						=			next_ncol // 2
          return dft[0]


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					int						=			self.__dft('A')
          __A		:					Optional[Any]						=			self.__dft('B')
          __A		:					str						=			[[dft_a[i] * dft_b[i] for i in range(self.c_max_length)]]
          del dft_a
          del dft_b

          # Corner Case
          if len(inverce_c[0]) <= 1:
               return inverce_c[0]
          # Inverse DFT
          __A		:					Dict						=			2
          while next_ncol <= self.c_max_length:
               __A		:					Optional[int]						=			[[] for i in range(_UpperCAmelCase)]
               __A		:					Any						=			self.root ** (next_ncol // 2)
               __A		:					Tuple						=			1
               # First half of next step
               for j in range(self.c_max_length // next_ncol):
                    for i in range(next_ncol // 2):
                         # Even positions
                         new_inverse_c[i].append(
                             (
                                 inverce_c[i][j]
                                 + inverce_c[i][j + self.c_max_length // next_ncol]
                             )
                             / 2)
                         # Odd positions
                         new_inverse_c[i + next_ncol // 2].append(
                             (
                                 inverce_c[i][j]
                                 - inverce_c[i][j + self.c_max_length // next_ncol]
                             )
                             / (2 * current_root))
                    current_root *= root
               # Update
               __A		:					int						=			new_inverse_c
               next_ncol *= 2
          # Unpack
          __A		:					Optional[int]						=			[round(x[0].real		,      8) + round(x[0].imag		,      8) * 1j for x in inverce_c]

          # Remove leading 0's
          while inverce_c[-1] == 0:
               inverce_c.pop()
          return inverce_c


     def __str__(		self):

          '''simple docstring'''






          __A		:					int						=			'A = ' + ' + '.join(
              F'{coef}*x^{i}' for coef, i in enumerate(self.polyA[: self.len_A]))
          __A		:					Optional[Any]						=			'B = ' + ' + '.join(
              F'{coef}*x^{i}' for coef, i in enumerate(self.polyB[: self.len_B]))
          __A		:					str						=			'A*B = ' + ' + '.join(
              F'{coef}*x^{i}' for coef, i in enumerate(self.product))

          return F'{a}\n{b}\n{c}'


# Unit tests
if __name__ == "__main__":
  import doctest

  doctest.testmod()