






'''simple docstring'''



import argparse
import os
import re


SCREAMING_SNAKE_CASE						=	'src/diffusers'

# Pattern that looks at the indentation in a line.
SCREAMING_SNAKE_CASE						=	re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
SCREAMING_SNAKE_CASE						=	re.compile(r'^\s*"([^"]+)":')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
SCREAMING_SNAKE_CASE						=	re.compile(r'^\s*_import_structure\["([^"]+)"\]')
# Pattern that matches `"key",` and puts `key` in group 0.
SCREAMING_SNAKE_CASE						=	re.compile(r'^\s*"([^"]+)",\s*$')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
SCREAMING_SNAKE_CASE						=	re.compile(r'\[([^\]]+)\]')


def 							lowercase_				(    __A :       Optional[Any]			)       ->      Union[str, Any]:



 """simple docstring"""




 lowercase					:   Dict				  =_re_indent.search(__A			)
 return "" if search is None else search.groups()[0]


def 							lowercase_				(    __A :       List[str]					,      __A :       Tuple=""					,      __A :       List[str]=None					,      __A :       Dict=None			)       ->      str:



 """simple docstring"""




 lowercase					:   List[str]				  =0
 lowercase					:   List[Any]				  =code.split('''\n'''			)
 if start_prompt is not None:
  while not lines[index].startswith(__A			):
   index += 1
  lowercase					:   Tuple				  =['''\n'''.join(lines[:index]			)]
 else:
  lowercase					:   Optional[Any]				  =[]

 # We split into blocks until we get to the `end_prompt` (or the end of the block).
 lowercase					:   List[str]				  =[lines[index]]
 index += 1
 while index < len(__A			) and (end_prompt is None or not lines[index].startswith(__A			)):
  if len(lines[index]			) > 0 and get_indent(lines[index]			) == indent_level:
   if len(__A			) > 0 and get_indent(current_block[-1]			).startswith(indent_level + ''' '''			):
    current_block.append(lines[index]			)
    blocks.append('''\n'''.join(__A			)			)
    if index < len(__A			) - 1:
     lowercase					:   Tuple				  =[lines[index + 1]]
     index += 1
    else:
     lowercase					:   List[Any]				  =[]
   else:
    blocks.append('''\n'''.join(__A			)			)
    lowercase					:   Any				  =[lines[index]]
  else:
   current_block.append(lines[index]			)
  index += 1

 # Adds current block if it's nonempty.
 if len(__A			) > 0:
  blocks.append('''\n'''.join(__A			)			)

 # Add final block after end_prompt if provided.
 if end_prompt is not None and index < len(__A			):
  blocks.append('''\n'''.join(lines[index:]			)			)

 return blocks


def 							lowercase_				(    __A :       List[Any]			)       ->      Union[str, Any]:



 """simple docstring"""




 def _inner(__A :       Tuple			):
  return key(__A			).lower().replace('''_'''					,      ''''''			)

 return _inner


def 							lowercase_				(    __A :       str					,      __A :       Union[str, Any]=None			)       ->      Union[str, Any]:



 """simple docstring"""




 def noop(__A :       Optional[Any]			):
  return x

 if key is None:
  lowercase					:   str				  =noop
 # Constants are all uppercase, they go first.
 lowercase					:   int				  =[obj for obj in objects if key(__A			).isupper()]
 # Classes are not all uppercase but start with a capital, they go second.
 lowercase					:   Tuple				  =[obj for obj in objects if key(__A			)[0].isupper() and not key(__A			).isupper()]
 # Functions begin with a lowercase, they go last.
 lowercase					:   List[str]				  =[obj for obj in objects if not key(__A			)[0].isupper()]

 lowercase					:   Dict				  =ignore_underscore(__A			)
 return sorted(__A					,      key=__A			) + sorted(__A					,      key=__A			) + sorted(__A					,      key=__A			)


def 							lowercase_				(    __A :       Union[str, Any]			)       ->      int:



 """simple docstring"""




 def _replace(__A :       List[str]			):
  lowercase					:   Dict				  =match.groups()[0]
  if "," not in imports:
   return F'[{imports}]'
  lowercase					:   Union[str, Any]				  =[part.strip().replace('''"'''					,      ''''''			) for part in imports.split(''','''			)]
  # We will have a final empty element if the line finished with a comma.
  if len(keys[-1]			) == 0:
   lowercase					:   Any				  =keys[:-1]
  return "[" + ", ".join([F'"{k}"' for k in sort_objects(__A			)]			) + "]"

 lowercase					:   Tuple				  =import_statement.split('''\n'''			)
 if len(__A			) > 3:
  # Here we have to sort internal imports that are on several lines (one per name):
  # key: [
  #     "object1",
  #     "object2",
  #     ...
  # ]

  # We may have to ignore one or two lines on each side.
  lowercase					:   int				  =2 if lines[1].strip() == '''[''' else 1
  lowercase					:   List[str]				  =[(i, _re_strip_line.search(__A			).groups()[0]) for i, line in enumerate(lines[idx:-idx]			)]
  lowercase					:   Tuple				  =sort_objects(__A					,      key=lambda __A			: x[1]			)
  lowercase					:   List[Any]				  =[lines[x[0] + idx] for x in sorted_indices]
  return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]			)
 elif len(__A			) == 3:
  # Here we have to sort internal imports that are on one separate line:
  # key: [
  #     "object1", "object2", ...
  # ]
  if _re_bracket_content.search(lines[1]			) is not None:
   lowercase					:   Union[str, Any]				  =_re_bracket_content.sub(_replace					,      lines[1]			)
  else:
   lowercase					:   List[str]				  =[part.strip().replace('''"'''					,      ''''''			) for part in lines[1].split(''','''			)]
   # We will have a final empty element if the line finished with a comma.
   if len(keys[-1]			) == 0:
    lowercase					:   Union[str, Any]				  =keys[:-1]
   lowercase					:   Optional[int]				  =get_indent(lines[1]			) + ''', '''.join([F'"{k}"' for k in sort_objects(__A			)]			)
  return "\n".join(__A			)
 else:
  # Finally we have to deal with imports fitting on one line
  lowercase					:   Optional[Any]				  =_re_bracket_content.sub(_replace					,      __A			)
  return import_statement


def 							lowercase_				(    __A :       int					,      __A :       int=True			)       ->      int:



 """simple docstring"""




 with open(__A					,      '''r'''			) as f:
  lowercase					:   Optional[Any]				  =f.read()

 if "_import_structure" not in code:
  return

 # Blocks of indent level 0
 lowercase					:   Tuple				  =split_code_in_indented_blocks(
     __A					,      start_prompt='''_import_structure = {'''					,      end_prompt='''if TYPE_CHECKING:'''			)

 # We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
 for block_idx in range(1					,      len(__A			) - 1			):
  # Check if the block contains some `_import_structure`s thingy to sort.
  lowercase					:   int				  =main_blocks[block_idx]
  lowercase					:   List[Any]				  =block.split('''\n'''			)

  # Get to the start of the imports.
  lowercase					:   List[str]				  =0
  while line_idx < len(__A			) and "_import_structure" not in block_lines[line_idx]:
   # Skip dummy import blocks
   if "import dummy" in block_lines[line_idx]:
    lowercase					:   int				  =len(__A			)
   else:
    line_idx += 1
  if line_idx >= len(__A			):
   continue

  # Ignore beginning and last line: they don't contain anything.
  lowercase					:   int				  ='''\n'''.join(block_lines[line_idx:-1]			)
  lowercase					:   List[Any]				  =get_indent(block_lines[1]			)
  # Slit the internal block into blocks of indent level 1.
  lowercase					:   int				  =split_code_in_indented_blocks(__A					,      indent_level=__A			)
  # We have two categories of import key: list or _import_structure[key].append/extend
  lowercase					:   List[str]				  =_re_direct_key if '''_import_structure''' in block_lines[0] else _re_indirect_key
  # Grab the keys, but there is a trap: some lines are empty or just comments.
  lowercase					:   int				  =[(pattern.search(__A			).groups()[0] if pattern.search(__A			) is not None else None) for b in internal_blocks]
  # We only sort the lines with a key.
  lowercase					:   List[Any]				  =[(i, key) for i, key in enumerate(__A			) if key is not None]
  lowercase					:   Optional[int]				  =[x[0] for x in sorted(__A					,      key=lambda __A			: x[1]			)]

  # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
  lowercase					:   Optional[Any]				  =0
  lowercase					:   str				  =[]
  for i in range(len(__A			)			):
   if keys[i] is None:
    reordered_blocks.append(internal_blocks[i]			)
   else:
    lowercase					:   Optional[Any]				  =sort_objects_in_import(internal_blocks[sorted_indices[count]]			)
    reordered_blocks.append(__A			)
    count += 1

        # And we put our main block back together with its first and last line.
  lowercase					:   Any				  ='''\n'''.join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]			)

 if code != "\n".join(__A			):
  if check_only:
   return True
  else:
   print(F'Overwriting {file}.'			)
   with open(__A					,      '''w'''			) as f:
    f.write('''\n'''.join(__A			)			)


def 							lowercase_				(    __A :       Tuple=True			)       ->      List[str]:



 """simple docstring"""




 lowercase					:   Tuple				  =[]
 for root, _, files in os.walk(__A			):
  if "__init__.py" in files:
   lowercase					:   Optional[int]				  =sort_imports(os.path.join(__A					,      '''__init__.py'''			)					,      check_only=__A			)
   if result:
    lowercase					:   Optional[Any]				  =[os.path.join(__A					,      '''__init__.py'''			)]
 if len(__A			) > 0:
  raise ValueError(F'Would overwrite {len(__A			)} files, run `make style`.'			)


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

      sort_imports_in_all_inits(check_only=args.check_only)











'''simple docstring'''



import unittest

from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_detectrona,
    require_pytesseract,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
      from PIL import Image

      from transformers.image_utils import load_image
else:
      class UpperCAmelCase_					:




            """simple docstring"""




            @staticmethod
            def 				A__      ( *UpperCAmelCase			:		Union[str, Any]     ,      **UpperCAmelCase			:		Optional[int]		)  ->  Any:


             '''simple docstring'''

             pass





      def 							lowercase_				(    __A :       Union[str, Any]			)       ->      List[Any]:



       """simple docstring"""




       return None


# This is a pinned image from a specific revision of a document question answering space, hosted by HuggingFace,
# so we can expect it to be available.
SCREAMING_SNAKE_CASE						=	(
    'https://huggingface.co/spaces/impira/docquery/resolve/2f6c96314dc84dfda62d40de9da55f2f5165d403/invoice.png'
)
@is_pipeline_test
@require_torch
@require_vision
class UpperCAmelCase_					(    unittest.TestCase				):




      """simple docstring"""




      UpperCamelCase_								=			MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING






      @require_pytesseract
      @require_vision
      def 				A__      ( self			:		Union[str, Any]     ,      UpperCAmelCase			:		Dict     ,      UpperCAmelCase			:		str     ,      UpperCAmelCase			:		List[str]		)  ->  Tuple:


       '''simple docstring'''

       lowercase					:   Dict				  =pipeline(
           '''document-question-answering'''     ,      model=UpperCAmelCase     ,      tokenizer=UpperCAmelCase     ,      image_processor=UpperCAmelCase		)

       lowercase					:   Optional[Any]				  =INVOICE_URL
       lowercase					:   Any				  =list(zip(*apply_tesseract(load_image(UpperCAmelCase		)     ,      UpperCAmelCase     ,      ''''''		)		)		)
       lowercase					:   Dict				  ='''What is the placebo?'''
       lowercase					:   Optional[Any]				  =[
           {
               '''image''': load_image(UpperCAmelCase		),
               '''question''': question,
           },
           {
               '''image''': image,
               '''question''': question,
           },
           {
               '''image''': image,
               '''question''': question,
               '''word_boxes''': word_boxes,
           },
       ]
       return dqa_pipeline, examples






      def 				A__      ( self			:		Any     ,      UpperCAmelCase			:		Optional[int]     ,      UpperCAmelCase			:		int		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   Dict				  =dqa_pipeline(UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(
           UpperCAmelCase     ,      [
               [
                   {'''score''': ANY(UpperCAmelCase		), '''answer''': ANY(UpperCAmelCase		), '''start''': ANY(UpperCAmelCase		), '''end''': ANY(UpperCAmelCase		)},
                   {'''score''': ANY(UpperCAmelCase		), '''answer''': ANY(UpperCAmelCase		), '''start''': ANY(UpperCAmelCase		), '''end''': ANY(UpperCAmelCase		)},
               ]
           ]
           * 3     ,      )






      @require_torch
      @require_detectrona
      @require_pytesseract
      def 				A__      ( self			:		int		)  ->  Any:


       '''simple docstring'''

       lowercase					:   Dict				  =pipeline('''document-question-answering'''     ,      model='''hf-internal-testing/tiny-random-layoutlmv2'''		)
       lowercase					:   Union[str, Any]				  =INVOICE_URL
       lowercase					:   Tuple				  ='''How many cats are there?'''

       lowercase					:   Optional[int]				  =[
           {'''score''': 0.0_0_0_1, '''answer''': '''oy 2312/2019''', '''start''': 38, '''end''': 39},
           {'''score''': 0.0_0_0_1, '''answer''': '''oy 2312/2019 DUE''', '''start''': 38, '''end''': 40},
       ]
       lowercase					:   Optional[Any]				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      UpperCAmelCase		)

       lowercase					:   List[str]				  =dqa_pipeline({'''image''': image, '''question''': question}     ,      top_k=2		)
       self.assertEqual(nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      UpperCAmelCase		)

       # This image does not detect ANY text in it, meaning layoutlmv2 should fail.
       # Empty answer probably
       lowercase					:   Optional[Any]				  ='''./tests/fixtures/tests_samples/COCO/000000039769.png'''
       lowercase					:   Any				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(UpperCAmelCase     ,      []		)

       # We can optionnally pass directly the words and bounding boxes
       lowercase					:   int				  ='''./tests/fixtures/tests_samples/COCO/000000039769.png'''
       lowercase					:   Dict				  =[]
       lowercase					:   str				  =[]
       lowercase					:   str				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      words=UpperCAmelCase     ,      boxes=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(UpperCAmelCase     ,      []		)






      @slow
      @require_torch
      @require_detectrona
      @require_pytesseract
      def 				A__      ( self			:		int		)  ->  Any:


       '''simple docstring'''

       lowercase					:   Union[str, Any]				  =pipeline(
           '''document-question-answering'''     ,      model='''tiennvcs/layoutlmv2-base-uncased-finetuned-docvqa'''     ,      revision='''9977165'''     ,      )
       lowercase					:   Dict				  =INVOICE_URL
       lowercase					:   str				  ='''What is the invoice number?'''

       lowercase					:   List[str]				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.9_9_4_4, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.0_0_0_9, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
           ]     ,      )

       lowercase					:   List[Any]				  =dqa_pipeline({'''image''': image, '''question''': question}     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.9_9_4_4, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.0_0_0_9, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
           ]     ,      )

       lowercase					:   List[Any]				  =dqa_pipeline(
           [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               [
                   {'''score''': 0.9_9_4_4, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
                   {'''score''': 0.0_0_0_9, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               ],
           ]
           * 2     ,      )






      @slow
      @require_torch
      @require_detectrona
      @require_pytesseract
      def 				A__      ( self			:		Dict		)  ->  List[str]:


       '''simple docstring'''

       lowercase					:   str				  =pipeline(
           '''document-question-answering'''     ,      model='''tiennvcs/layoutlmv2-base-uncased-finetuned-docvqa'''     ,      revision='''9977165'''     ,      max_seq_len=50     ,      )
       lowercase					:   Dict				  =INVOICE_URL
       lowercase					:   Any				  ='''What is the invoice number?'''

       lowercase					:   Union[str, Any]				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.9_9_7_4, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
               {'''score''': 0.9_9_4_8, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
           ]     ,      )

       lowercase					:   int				  =dqa_pipeline({'''image''': image, '''question''': question}     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.9_9_7_4, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
               {'''score''': 0.9_9_4_8, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
           ]     ,      )

       lowercase					:   Any				  =dqa_pipeline(
           [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               [
                   {'''score''': 0.9_9_7_4, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
                   {'''score''': 0.9_9_4_8, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               ]
           ]
           * 2     ,      )






      @slow
      @require_torch
      @require_pytesseract
      @require_vision
      def 				A__      ( self			:		str		)  ->  Dict:


       '''simple docstring'''

       lowercase					:   Any				  =AutoTokenizer.from_pretrained(
           '''impira/layoutlm-document-qa'''     ,      revision='''3dc6de3'''     ,      add_prefix_space=UpperCAmelCase		)
       lowercase					:   Tuple				  =pipeline(
           '''document-question-answering'''     ,      model='''impira/layoutlm-document-qa'''     ,      tokenizer=UpperCAmelCase     ,      revision='''3dc6de3'''     ,      )
       lowercase					:   Tuple				  =INVOICE_URL
       lowercase					:   Any				  ='''What is the invoice number?'''

       lowercase					:   Dict				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.4_2_5_1, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.0_8_1_9, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
           ]     ,      )

       lowercase					:   Any				  =dqa_pipeline({'''image''': image, '''question''': question}     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.4_2_5_1, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.0_8_1_9, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
           ]     ,      )

       lowercase					:   str				  =dqa_pipeline(
           [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               [
                   {'''score''': 0.4_2_5_1, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
                   {'''score''': 0.0_8_1_9, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
               ]
           ]
           * 2     ,      )

       lowercase					:   Tuple				  =list(zip(*apply_tesseract(load_image(UpperCAmelCase		)     ,      UpperCAmelCase     ,      ''''''		)		)		)

       # This model should also work if `image` is set to None
       lowercase					:   Dict				  =dqa_pipeline({'''image''': None, '''word_boxes''': word_boxes, '''question''': question}     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.4_2_5_1, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.0_8_1_9, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
           ]     ,      )






      @slow
      @require_torch
      @require_pytesseract
      @require_vision
      def 				A__      ( self			:		Dict		)  ->  Any:


       '''simple docstring'''

       lowercase					:   Dict				  =AutoTokenizer.from_pretrained(
           '''impira/layoutlm-document-qa'''     ,      revision='''3dc6de3'''     ,      add_prefix_space=UpperCAmelCase		)
       lowercase					:   List[Any]				  =pipeline(
           '''document-question-answering'''     ,      model='''impira/layoutlm-document-qa'''     ,      tokenizer=UpperCAmelCase     ,      revision='''3dc6de3'''     ,      max_seq_len=50     ,      )
       lowercase					:   str				  =INVOICE_URL
       lowercase					:   int				  ='''What is the invoice number?'''

       lowercase					:   Tuple				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.9_9_9_9, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.9_9_9_8, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
           ]     ,      )

       lowercase					:   Union[str, Any]				  =dqa_pipeline(
           [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               [
                   {'''score''': 0.9_9_9_9, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
                   {'''score''': 0.9_9_9_8, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               ]
           ]
           * 2     ,      )

       lowercase					:   List[str]				  =list(zip(*apply_tesseract(load_image(UpperCAmelCase		)     ,      UpperCAmelCase     ,      ''''''		)		)		)

       # This model should also work if `image` is set to None
       lowercase					:   Union[str, Any]				  =dqa_pipeline({'''image''': None, '''word_boxes''': word_boxes, '''question''': question}     ,      top_k=2		)
       self.assertEqual(
           nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [
               {'''score''': 0.9_9_9_9, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
               {'''score''': 0.9_9_9_8, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
           ]     ,      )






      @slow
      @require_torch
      def 				A__      ( self			:		List[Any]		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   str				  =pipeline(
           '''document-question-answering'''     ,      model='''naver-clova-ix/donut-base-finetuned-docvqa'''     ,      tokenizer=AutoTokenizer.from_pretrained('''naver-clova-ix/donut-base-finetuned-docvqa'''		)     ,      feature_extractor='''naver-clova-ix/donut-base-finetuned-docvqa'''     ,      )

       lowercase					:   Any				  =INVOICE_URL
       lowercase					:   Union[str, Any]				  ='''What is the invoice number?'''
       lowercase					:   int				  =dqa_pipeline(image=UpperCAmelCase     ,      question=UpperCAmelCase     ,      top_k=2		)
       self.assertEqual(nested_simplify(UpperCAmelCase     ,      decimals=4		)     ,      [{'''answer''': '''us-001'''}]		)






      @require_tf
      @unittest.skip('''Document question answering not implemented in TF'''		)
      def 				A__      ( self			:		Any		)  ->  Any:


       '''simple docstring'''

       pass



