





'''simple docstring'''
from math import factorial

class      snake_case     :




 """simple docstring"""



 def __init__(       self       :							List[str]							,	__A       :							Any							,	__A       :							Tuple	):
        __UpperCamelCase       =  real
        if isinstance(__A							,	__A	):
               __UpperCamelCase       =  [1] * rank
        else:
               __UpperCamelCase       =  rank






 def __repr__(       self       :							Any	):
        return (
            f'''{self.real}+'''
            f'''{'+'.join(str(__A	)+'E'+str(n+1	)for n,dual in enumerate(self.duals	)	)}'''
        )






 def        _lowerCamelCase					(       self       :							str	):
        __UpperCamelCase       =  self.duals.copy()
        while cur[-1] == 0:
               cur.pop(-1	)
        return Dual(self.real							,	__A	)






 def __add__(       self       :							List[Any]							,	__A       :							Any	):
        if not isinstance(__A							,	__A	):
               return Dual(self.real + other							,	self.duals	)
        __UpperCamelCase       =  self.duals.copy()
        __UpperCamelCase       =  other.duals.copy()
        if len(__A	) > len(__A	):
               o_dual.extend([1] * (len(__A	) - len(__A	))	)
        elif len(__A	) < len(__A	):
               s_dual.extend([1] * (len(__A	) - len(__A	))	)
        __UpperCamelCase       =  []
        for i in range(len(__A	)	):
               new_duals.append(s_dual[i] + o_dual[i]	)
        return Dual(self.real + other.real							,	__A	)

 SCREAMING_SNAKE_CASE_	:					Tuple					=__add__






 def __sub__(       self       :							List[str]							,	__A       :							List[Any]	):
        return self + other * -1






 def __mul__(       self       :							Tuple							,	__A       :							List[str]	):
        if not isinstance(__A							,	__A	):
               __UpperCamelCase       =  []
               for i in self.duals:
                      new_duals.append(i * other	)
               return Dual(self.real * other							,	__A	)
        __UpperCamelCase       =  [0] * (len(self.duals	) + len(other.duals	) + 1)
        for i, item in enumerate(self.duals	):
               for j, jtem in enumerate(other.duals	):
                      new_duals[i + j + 1] += item * jtem
        for k in range(len(self.duals	)	):
               new_duals[k] += self.duals[k] * other.real
        for index in range(len(other.duals	)	):
               new_duals[index] += other.duals[index] * self.real
        return Dual(self.real * other.real							,	__A	)

 SCREAMING_SNAKE_CASE_	:					Optional[Any]					=__mul__






 def __truediv__(       self       :							int							,	__A       :							List[str]	):
        if not isinstance(__A							,	__A	):
               __UpperCamelCase       =  []
               for i in self.duals:
                      new_duals.append(i / other	)
               return Dual(self.real / other							,	__A	)
        raise ValueError






 def __floordiv__(       self       :							Any							,	__A       :							List[Any]	):
        if not isinstance(__A							,	__A	):
               __UpperCamelCase       =  []
               for i in self.duals:
                      new_duals.append(i // other	)
               return Dual(self.real // other							,	__A	)
        raise ValueError






 def __pow__(       self       :							str							,	__A       :							Optional[int]	):
        if n < 0 or isinstance(__A							,	__A	):
               raise ValueError('power must be a positive integer'	)
        if n == 0:
               return 1
        if n == 1:
               return self
        __UpperCamelCase       =  self
        for _ in range(n - 1	):
               x *= self
        return x






def 				lowercase__   (   __lowercase						:  str				,  __lowercase						:  Optional[int]				,  __lowercase						:  List[str]     ) ->      Dict:



       """simple docstring"""






       if not callable(__lowercase     ):
              raise ValueError('differentiate() requires a function as input for func'     )
       if not isinstance(__lowercase				,  (float, int)     ):
              raise ValueError('differentiate() requires a float as input for position'     )
       if not isinstance(__lowercase				,  __lowercase     ):
              raise ValueError('differentiate() requires an int as input for order'     )
       __UpperCamelCase       =  Dual(__lowercase				,  1     )
       __UpperCamelCase       =  func(__lowercase     )
       if order == 0:
              return result.real
       return result.duals[order - 1] * factorial(__lowercase     )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    def 				lowercase__   (   __lowercase						:  Optional[int]     ) ->      List[Any]:



           """simple docstring"""






           return y**2 * y**4


    print(differentiate(f, 9, 2))







'''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      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					Tuple					="naver-clova-ix/donut-base-finetuned-docvqa"
 SCREAMING_SNAKE_CASE_	:					Dict					=(
     "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."
 )
 SCREAMING_SNAKE_CASE_	:					List[str]					="document_qa"
 SCREAMING_SNAKE_CASE_	:					Union[str, Any]					=AutoProcessor
 SCREAMING_SNAKE_CASE_	:					Union[str, Any]					=VisionEncoderDecoderModel

 SCREAMING_SNAKE_CASE_	:					List[Any]					=["image", "text"]
 SCREAMING_SNAKE_CASE_	:					Any					=["text"]






 def __init__(       self       :							Optional[int]							,	*__A       :							List[str]							,	**__A       :							List[Any]	):
        if not is_vision_available():
               raise ValueError('Pillow must be installed to use the DocumentQuestionAnsweringTool.'	)

        super().__init__(*__A							,	**__A	)






 def        _lowerCamelCase					(       self       :							Any							,	__A       :							"Image"							,	__A       :							str	):
        __UpperCamelCase       =  '<s_docvqa><s_question>{user_input}</s_question><s_answer>'
        __UpperCamelCase       =  task_prompt.replace('{user_input}'							,	__A	)
        __UpperCamelCase       =  self.pre_processor.tokenizer(
            __A							,	add_special_tokens=__A							,	return_tensors='pt'	).input_ids
        __UpperCamelCase       =  self.pre_processor(__A							,	return_tensors='pt'	).pixel_values

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






 def        _lowerCamelCase					(       self       :							Union[str, Any]							,	__A       :							Optional[Any]	):
        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       :							Tuple							,	__A       :							List[Any]	):
        __UpperCamelCase       =  self.pre_processor.batch_decode(__A	)[0]
        __UpperCamelCase       =  sequence.replace(self.pre_processor.tokenizer.eos_token							,	''	)
        __UpperCamelCase       =  sequence.replace(self.pre_processor.tokenizer.pad_token							,	''	)
        __UpperCamelCase       =  re.sub(R'<.*?>'							,	''							,	__A							,	count=1	).strip()  # remove first task start token
        __UpperCamelCase       =  self.pre_processor.tokenajson(__A	)

        return sequence["answer"]
