

# 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							(							__A      ):
			'''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							:       List[str]					,					*a							:       List[Any]					,					**a							:       Any		)							->				Optional[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							:       List[Any]					,					a							:       "Image"					,					a							:       str		)							->				Dict:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE      :					List[str]    =				"<s_docvqa><s_question>{user_input}</s_question><s_answer>"
				SCREAMING_SNAKE_CASE      :					Any    =				task_prompt.replace("{user_input}"					,					a		)
				SCREAMING_SNAKE_CASE      :					List[Any]    =				self.pre_processor.tokenizer(
				    a					,					add_special_tokens=a					,					return_tensors="pt"		).input_ids
				SCREAMING_SNAKE_CASE      :					Optional[Any]    =				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							:       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							:       Tuple					,					a							:       Optional[Any]		)							->				int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE      :					Any    =				self.pre_processor.batch_decode(a		)[0]
				SCREAMING_SNAKE_CASE      :					Dict    =				sequence.replace(self.pre_processor.tokenizer.eos_token					,					""		)
				SCREAMING_SNAKE_CASE      :					int    =				sequence.replace(self.pre_processor.tokenizer.pad_token					,					""		)
				SCREAMING_SNAKE_CASE      :					List[Any]    =				re.sub(R"<.*?>"					,					""					,					a					,					count=1		).strip()  # remove first task start token
				SCREAMING_SNAKE_CASE      :					Any    =				self.pre_processor.tokenajson(a		)

				return sequence["answer"]

import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
lowercase__       ={
    'E': 12.70,
    'T': 9.06,
    'A': 8.17,
    'O': 7.51,
    'I': 6.97,
    'N': 6.75,
    'S': 6.33,
    'H': 6.09,
    'R': 5.99,
    'D': 4.25,
    'L': 4.03,
    'C': 2.78,
    'U': 2.76,
    'M': 2.41,
    'W': 2.36,
    'F': 2.23,
    'G': 2.02,
    'Y': 1.97,
    'P': 1.93,
    'B': 1.29,
    'V': 0.98,
    'K': 0.77,
    'J': 0.15,
    'X': 0.15,
    'Q': 0.10,
    'Z': 0.07,
}
lowercase__       ='ETAOINSHRDLCUMWFGYPBVKJXQZ'
lowercase__       ='ABCDEFGHIJKLMNOPQRSTUVWXYZ'




def    __UpperCamelCase     (				lowerCAmelCase__							:				str  ):
 __a :  List[Any]						=  {letter: 0 for letter in string.ascii_uppercase}
 for letter in message.upper():
  if letter in LETTERS:
   letter_count[letter] += 1

 return letter_count




def    __UpperCamelCase     (				lowerCAmelCase__							:				tuple  ):
 return x[0]




def    __UpperCamelCase     (				lowerCAmelCase__							:				str  ):
 __a :  Optional[Any]						=  get_letter_count(lowerCAmelCase__  )
 __a :  dict[int, list[str]]						=  {
     freq: [] for letter, freq in letter_to_freq.items()
 }
 for letter in LETTERS:
  freq_to_letter[letter_to_freq[letter]].append(lowerCAmelCase__  )

 __a :  dict[int, str]						=  {}

 for freq in freq_to_letter:
  freq_to_letter[freq].sort(key=ETAOIN.find  ,   reverse=lowerCAmelCase__  )
  __a :  int						=  ''''''.join(freq_to_letter[freq]  )

 __a :  Any						=  list(freq_to_letter_str.items()  )
 freq_pairs.sort(key=lowerCAmelCase__  ,   reverse=lowerCAmelCase__  )

 __a :  list[str]						=  [freq_pair[1] for freq_pair in freq_pairs]

 return "".join(lowerCAmelCase__  )




def    __UpperCamelCase     (				lowerCAmelCase__							:				str  ):
 __a :  int						=  get_frequency_order(lowerCAmelCase__  )
 __a :  str						=  0
 for common_letter in ETAOIN[:6]:
  if common_letter in freq_order[:6]:
   match_score += 1

 for uncommon_letter in ETAOIN[-6:]:
  if uncommon_letter in freq_order[-6:]:
   match_score += 1

 return match_score


if __name__ == "__main__":
      import doctest

      doctest.testmod()
