# 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__				(   UpperCAmelCase				):
			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	:	Tuple  ,  *lowercase__	:	List[Any]  ,  **lowercase__	:	int						):
										if not is_vision_available():
																	raise ValueError('Pillow must be installed to use the DocumentQuestionAnsweringTool.'						)

										super().__init__(*lowercase__  ,  **lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	Tuple  ,  lowercase__	:	"Image"  ,  lowercase__	:	str						):
										_lowerCAmelCase							=							'<s_docvqa><s_question>{user_input}</s_question><s_answer>'
										_lowerCAmelCase							=							task_prompt.replace('{user_input}'  ,  lowercase__						)
										_lowerCAmelCase							=							self.pre_processor.tokenizer(
										    lowercase__  ,  add_special_tokens=lowercase__  ,  return_tensors='pt'						).input_ids
										_lowerCAmelCase							=							self.pre_processor(lowercase__  ,  return_tensors='pt'						).pixel_values

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





			def   SCREAMING_SNAKE_CASE__     (       self	:	Dict  ,  lowercase__	:	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=lowercase__  ,  pad_token_id=self.pre_processor.tokenizer.pad_token_id  ,  eos_token_id=self.pre_processor.tokenizer.eos_token_id  ,  use_cache=lowercase__  ,  num_beams=1  ,  bad_words_ids=[[self.pre_processor.tokenizer.unk_token_id]]  ,  return_dict_in_generate=lowercase__  ,  ).sequences





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

										return sequence["answer"]







from math import ceil, sqrt






def _lowerCamelCase  (		snake_case = 1_000_000  ):
							_lowerCAmelCase							=							0

							for outer_width in range(3     , (limit // 4) + 2  ):
														if outer_width**2 > limit:
																					_lowerCAmelCase							=							max(ceil(sqrt(outer_width**2 - limit  )  )     , 1  )
														else:
																					_lowerCAmelCase							=							1
														if (outer_width - hole_width_lower_bound) % 2:
																					hole_width_lower_bound += 1

														answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

							return answer


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






