




# 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   (				UpperCAmelCase__			):







						'''simple docstring'''





						lowerCAmelCase_     		=   '''naver-clova-ix/donut-base-finetuned-docvqa'''
						lowerCAmelCase_     		=   (
						    '''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.'''
						)
						lowerCAmelCase_     		=   '''document_qa'''
						lowerCAmelCase_     		=   AutoProcessor
						lowerCAmelCase_     		=   VisionEncoderDecoderModel

						lowerCAmelCase_     		=   ['''image''', '''text''']
						lowerCAmelCase_     		=   ['''text''']






						def __init__(						self							:     Dict       ,	*__lowercase							:     Union[str, Any]       ,	**__lowercase							:     Optional[Any]						):






							"""simple docstring"""






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

							super().__init__(*__lowercase       ,	**__lowercase						)






						def        snake_case__						(						self							:     str       ,	__lowercase							:     "Image"       ,	__lowercase							:     str						):






							"""simple docstring"""






							snake_case_		    =     "<s_docvqa><s_question>{user_input}</s_question><s_answer>"
							snake_case_		    =     task_prompt.replace("{user_input}"       ,	__lowercase						)
							snake_case_		    =     self.pre_processor.tokenizer(
							    __lowercase       ,	add_special_tokens=__lowercase       ,	return_tensors="pt"						).input_ids
							snake_case_		    =     self.pre_processor(__lowercase       ,	return_tensors="pt"						).pixel_values

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






						def        snake_case__						(						self							:     int       ,	__lowercase							:     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=__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        snake_case__						(						self							:     Dict       ,	__lowercase							:     Any						):






							"""simple docstring"""






							snake_case_		    =     self.pre_processor.batch_decode(__lowercase						)[0]
							snake_case_		    =     sequence.replace(self.pre_processor.tokenizer.eos_token       ,	""						)
							snake_case_		    =     sequence.replace(self.pre_processor.tokenizer.pad_token       ,	""						)
							snake_case_		    =     re.sub(r"<.*?>"       ,	""       ,	__lowercase       ,	count=1						).strip()  # remove first task start token
							snake_case_		    =     self.pre_processor.tokenajson(__lowercase						)

							return sequence["answer"]






def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     len(_A							)
	for i in range(_A							):
		for j in range(i + 1     ,	_A							):
			if numbers[j] < numbers[i]:
				snake_case_    ,      snake_case_		    =     numbers[j], numbers[i]
	return numbers


if __name__ == "__main__":
		lowercase__				:     int 		=						input("Enter numbers separated by a comma:\n").strip()
		lowercase__				:     Any 		=						[int(item) for item in user_input.split(",")]
		print(exchange_sort(unsorted))
