
from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst





def 			lowerCamelCase_ (				):
				lowerCamelCase_	,    lowerCamelCase_						=			9, 1_4  # noqa: F841
				lowerCamelCase_						=			[
				    [0, 1, 4],
				    [0, 7, 8],
				    [1, 2, 8],
				    [7, 8, 7],
				    [7, 6, 1],
				    [2, 8, 2],
				    [8, 6, 6],
				    [2, 3, 7],
				    [2, 5, 4],
				    [6, 5, 2],
				    [3, 5, 1_4],
				    [3, 4, 9],
				    [5, 4, 1_0],
				    [1, 7, 1_1],
				]

				lowerCamelCase_						=			defaultdict(lowerCamelCase__    )
				for nodea, nodea, cost in edges:
								adjancency[nodea].append([nodea, cost]    )
								adjancency[nodea].append([nodea, cost]    )

				lowerCamelCase_						=			mst(lowerCamelCase__    )

				lowerCamelCase_						=			[
				    [7, 6, 1],
				    [2, 8, 2],
				    [6, 5, 2],
				    [0, 1, 4],
				    [2, 5, 4],
				    [2, 3, 7],
				    [0, 7, 8],
				    [3, 4, 9],
				]

				for answer in expected:
								lowerCamelCase_						=			tuple(answer[:2]    )
								lowerCamelCase_						=			tuple(edge[::-1]    )
								assert edge in result or reverse in result










# 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   (       __a	):

					'''simple docstring'''

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

					_A  :	Optional[int]     =					['''image''', '''text''']
					_A  :	Optional[int]     =					['''text''']



					def __init__(     self :		Any						,   *__a :		List[str]						,   **__a :		Any							)	->     Optional[Any]:


												"""simple docstring"""

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

												super().__init__(*__a						,   **__a							)



					def 					lowerCAmelCase (     self :		List[Any]						,   __a :		"Image"						,   __a :		str							)	->     List[str]:


												"""simple docstring"""

												__lowercase					:							int			=   """<s_docvqa><s_question>{user_input}</s_question><s_answer>"""
												__lowercase					:							str			=   task_prompt.replace("""{user_input}"""						,   __a							)
												__lowercase					:							Union[str, Any]			=   self.pre_processor.tokenizer(
												    __a						,   add_special_tokens=__a						,   return_tensors="""pt"""							).input_ids
												__lowercase					:							int			=   self.pre_processor(__a						,   return_tensors="""pt"""							).pixel_values

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



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


												"""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=__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 :		Union[str, Any]						,   __a :		Union[str, Any]							)	->     Union[str, Any]:


												"""simple docstring"""

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

												return sequence["answer"]