





'''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 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				__a            ='naver-clova-ix/donut-base-finetuned-docvqa'
				__a            =(
				    '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            ='document_qa'
				__a            =AutoProcessor
				__a            =VisionEncoderDecoderModel

				__a            =['image', 'text']
				__a            =['text']




				def __init__(  self     :					Optional[Any]					,				*__a     :					Any					,				**__a     :					Union[str, Any]					):
								if not is_vision_available():
												raise ValueError("Pillow must be installed to use the DocumentQuestionAnsweringTool."					)

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




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

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




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

								return sequence["answer"]







'''simple docstring'''







import argparse
import os
import re


lowerCAmelCase_					:    Any      	=			'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
lowerCAmelCase_					:    List[str]      	=			re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
lowerCAmelCase_					:    Tuple      	=			re.compile(R'\s*\(\s*"(\S[^"]+)"')






def  _lowerCamelCase				( lowercase						:      Any    ,							lowercase						:      bool = False						)	->	Optional[Any]:
				with open(lowercase    ,							"r"    ,							encoding="utf-8"						) as f:
								_a								= f.read()

				_a								= content.split("\n"						)
				_a								= []
				_a								= 0
				while line_idx < len(lowercase						):
								if _re_intro_mapping.search(lines[line_idx]						) is not None:
												_a								= len(re.search(r"^(\s*)\S"    ,							lines[line_idx]						).groups()[0]						) + 8
												# Start of a new mapping!
												while not lines[line_idx].startswith(" " * indent + "("						):
																new_lines.append(lines[line_idx]						)
																line_idx += 1

												_a								= []
												while lines[line_idx].strip() != "]":
																# Blocks either fit in one line or not
																if lines[line_idx].strip() == "(":
																				_a								= line_idx
																				while not lines[line_idx].startswith(" " * indent + ")"						):
																								line_idx += 1
																				blocks.append("\n".join(lines[start_idx : line_idx + 1]						)						)
																else:
																				blocks.append(lines[line_idx]						)
																line_idx += 1

												# Sort blocks by their identifiers
												_a								= sorted(lowercase    ,							key=lambda lowercase						: _re_identifier.search(lowercase						).groups()[0]						)
												new_lines += blocks
								else:
												new_lines.append(lines[line_idx]						)
												line_idx += 1

				if overwrite:
								with open(lowercase    ,							"w"    ,							encoding="utf-8"						) as f:
												f.write("\n".join(lowercase						)						)
				elif "\n".join(lowercase						) != content:
								return True






def  _lowerCamelCase				( lowercase						:      bool = False						)	->	List[str]:
				_a								= [os.path.join(lowercase    ,							lowercase						) for f in os.listdir(lowercase						) if f.endswith(".py"						)]
				_a								= [sort_auto_mapping(lowercase    ,							overwrite=lowercase						) for fname in fnames]

				if not overwrite and any(lowercase						):
								_a								= [f for f, d in zip(lowercase    ,							lowercase						) if d]
								raise ValueError(
								    F'The following files have auto mappings that need sorting: {", ".join(lowercase						)}. Run `make style` to fix'
								    " this."						)


if __name__ == "__main__":
					lowerCAmelCase_					:    Any      	=			argparse.ArgumentParser()
					parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
					lowerCAmelCase_					:    Optional[int]      	=			parser.parse_args()

					sort_all_auto_mappings(not args.check_only)
