


from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

snake_case_						:			Tuple													=							TypeVar('''KEY''')
snake_case_						:			Any													=							TypeVar('''VAL''')

@dataclass(frozen=_snake_case   ,     slots=_snake_case  )
class 						A__							(		Generic[KEY, VAL]  ):
						UpperCAmelCase             =						42
						UpperCAmelCase             =						42

class 						A__							(		_Item  ):




						def __init__(       self					:      Union[str, Any]  )							->     int:


										"""simple docstring"""





										super().__init__(snake_case_				,    snake_case_  )




						def __bool__(       self					:      Union[str, Any]  )							->     int:


										"""simple docstring"""





										return False
snake_case_						:			List[Any]													=							_DeletedItem()

class 						A__							(		MutableMapping[KEY, VAL]  ):




						def __init__(       self					:      Dict				,    _a					:      int = 8				,    _a					:      Optional[Any] = 0.75  )							->     List[Any]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =initial_block_size
										_SCREAMING_SNAKE_CASE			  =[None] * initial_block_size
										assert 0.0 < capacity_factor < 1.0
										_SCREAMING_SNAKE_CASE			  =capacity_factor
										_SCREAMING_SNAKE_CASE			  =0




						def 							__UpperCamelCase				(       self					:      Dict				,    _a					:      str  )							->     Optional[int]:


										"""simple docstring"""





										return hash(snake_case_  ) % len(self._buckets  )




						def 							__UpperCamelCase				(       self					:      int				,    _a					:      Any  )							->     int:


										"""simple docstring"""





										return (ind + 1) % len(self._buckets  )




						def 							__UpperCamelCase				(       self					:      Tuple				,    _a					:      Tuple				,    _a					:      List[str]				,    _a					:      Any  )							->     List[Any]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =self._buckets[ind]
										if not stored:
														_SCREAMING_SNAKE_CASE			  =_Item(snake_case_				,    snake_case_  )
														self._len += 1
														return True
										elif stored.key == key:
														_SCREAMING_SNAKE_CASE			  =_Item(snake_case_				,    snake_case_  )
														return True
										else:
														return False




						def 							__UpperCamelCase				(       self					:      int  )							->     Tuple:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =len(self._buckets  ) * self._capacity_factor
										return len(self  ) >= int(snake_case_  )




						def 							__UpperCamelCase				(       self					:      Any  )							->     Union[str, Any]:


										"""simple docstring"""





										if len(self._buckets  ) <= self._initial_block_size:
														return False
										_SCREAMING_SNAKE_CASE			  =len(self._buckets  ) * self._capacity_factor / 2
										return len(self  ) < limit




						def 							__UpperCamelCase				(       self					:      Union[str, Any]				,    _a					:      Optional[int]  )							->     str:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =self._buckets
										_SCREAMING_SNAKE_CASE			  =[None] * new_size
										_SCREAMING_SNAKE_CASE			  =0
										for item in old_buckets:
														if item:
																		self._add_item(item.key				,    item.val  )




						def 							__UpperCamelCase				(       self					:      int  )							->     Union[str, Any]:


										"""simple docstring"""





										self._resize(len(self._buckets  ) * 2  )




						def 							__UpperCamelCase				(       self					:      List[Any]  )							->     Optional[Any]:


										"""simple docstring"""





										self._resize(len(self._buckets  ) // 2  )




						def 							__UpperCamelCase				(       self					:      Tuple				,    _a					:      Dict  )							->     List[str]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =self._get_bucket_index(snake_case_  )
										for _ in range(len(self._buckets  )  ):
														yield ind
														_SCREAMING_SNAKE_CASE			  =self._get_next_ind(snake_case_  )




						def 							__UpperCamelCase				(       self					:      List[str]				,    _a					:      Optional[Any]				,    _a					:      Any  )							->     Optional[int]:


										"""simple docstring"""





										for ind in self._iterate_buckets(snake_case_  ):
														if self._try_set(snake_case_				,    snake_case_				,    snake_case_  ):
																		break




						def __setitem__(       self					:      List[Any]				,    _a					:      Tuple				,    _a					:      Tuple  )							->     str:


										"""simple docstring"""





										if self._is_full():
														self._size_up()

										self._add_item(snake_case_				,    snake_case_  )




						def __delitem__(       self					:      Optional[Any]				,    _a					:      Any  )							->     Dict:


										"""simple docstring"""





										for ind in self._iterate_buckets(snake_case_  ):
														_SCREAMING_SNAKE_CASE			  =self._buckets[ind]
														if item is None:
																		raise KeyError(snake_case_  )
														if item is _deleted:
																		continue
														if item.key == key:
																		_SCREAMING_SNAKE_CASE			  =_deleted
																		self._len -= 1
																		break
										if self._is_sparse():
														self._size_down()




						def __getitem__(       self					:      Any				,    _a					:      Dict  )							->     Union[str, Any]:


										"""simple docstring"""





										for ind in self._iterate_buckets(snake_case_  ):
														_SCREAMING_SNAKE_CASE			  =self._buckets[ind]
														if item is None:
																		break
														if item is _deleted:
																		continue
														if item.key == key:
																		return item.val
										raise KeyError(snake_case_  )




						def __len__(       self					:      str  )							->     Optional[int]:


										"""simple docstring"""





										return self._len




						def __iter__(       self					:      int  )							->     Any:


										"""simple docstring"""





										yield from (item.key for item in self._buckets if item)




						def __repr__(       self					:      Optional[int]  )							->     str:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =" ,".join(
										    f"{item.key}: {item.val}" for item in self._buckets if item  )
										return f"HashMap({val_string})"



# 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 						A__							(		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					:      Any				,    *_a					:      int				,    **_a					:      Dict  )							->     int:


										"""simple docstring"""





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

										super().__init__(*_a				,    **_a  )




						def 							__UpperCamelCase				(       self					:      Optional[Any]				,    _a					:      "Image"				,    _a					:      str  )							->     Tuple:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  ='''<s_docvqa><s_question>{user_input}</s_question><s_answer>'''
										_SCREAMING_SNAKE_CASE			  =task_prompt.replace('''{user_input}'''				,    _a  )
										_SCREAMING_SNAKE_CASE			  =self.pre_processor.tokenizer(
										    _a				,    add_special_tokens=_a				,    return_tensors='''pt'''  ).input_ids
										_SCREAMING_SNAKE_CASE			  =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					:      Optional[Any]  )							->     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 							__UpperCamelCase				(       self					:      Any				,    _a					:      int  )							->     Any:


										"""simple docstring"""





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

										return sequence["answer"]