# 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   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'naver-clova-ix/donut-base-finetuned-docvqa'
							_UpperCAmelCase						    =     (
							    '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						    =     'document_qa'
							_UpperCAmelCase						    =     AutoProcessor
							_UpperCAmelCase						    =     VisionEncoderDecoderModel

							_UpperCAmelCase						    =     ['image', 'text']
							_UpperCAmelCase						    =     ['text']







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

										super().__init__(*__snake_case	,					**__snake_case		)







							def 				snake_case  (				self     :    Dict	,					__snake_case     :    "Image"	,					__snake_case     :    str		):
										lowerCamelCase						:str						  =     '''<s_docvqa><s_question>{user_input}</s_question><s_answer>'''
										lowerCamelCase						:List[str]						  =     task_prompt.replace('''{user_input}'''	,					__snake_case		)
										lowerCamelCase						:Optional[int]						  =     self.pre_processor.tokenizer(
										    __snake_case	,					add_special_tokens=__snake_case	,					return_tensors='''pt'''		).input_ids
										lowerCamelCase						:str						  =     self.pre_processor(__snake_case	,					return_tensors='''pt'''		).pixel_values

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







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

										return sequence["answer"]




def  _lowerCamelCase					(   a_				: int = 4_00_00_00):
			lowerCamelCase						:Dict						  =     [0, 1]
			lowerCamelCase						:Optional[Any]						  =     0
			while fib[i] <= n:
						fib.append(fib[i] + fib[i + 1])
						if fib[i + 2] > n:
									break
						i += 1
			lowerCamelCase						:Dict						  =     0
			for j in range(len(a_) - 1):
						if fib[j] % 2 == 0:
									total += fib[j]

			return total


if __name__ == "__main__":
			print(F'{solution() = }')



