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 			__magic_name__	:





     """simple docstring"""




     @staticmethod
     def 	lowerCAmelCase    (						*_lowercase       :	Optional[Any]		,	**_lowercase       :	List[Any]				):



      """simple docstring"""



      pass




  def    lowerCAmelCase_  (		lowercase:				Any		)     ->					int:







   '''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.
UpperCAmelCase_           =				(
    '''https://huggingface.co/spaces/impira/docquery/resolve/2f6c96314dc84dfda62d40de9da55f2f5165d403/invoice.png'''
)




@is_pipeline_test
@require_torch
@require_vision
class 			__magic_name__	(		unittest.TestCase     ):





   """simple docstring"""




   lowerCAmelCase   :     Optional[int]	      = MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING



   @require_pytesseract
   @require_vision
   def 	lowerCAmelCase    (						self       :	Optional[int]		,	_lowercase       :	str		,	_lowercase       :	Optional[Any]		,	_lowercase       :	List[str]				):



    """simple docstring"""



    _UpperCamelCase:  str    						=			pipeline(
        '''document-question-answering'''		,	model=_lowercase		,	tokenizer=_lowercase		,	image_processor=_lowercase				)

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



   def 	lowerCAmelCase    (						self       :	Dict		,	_lowercase       :	List[Any]		,	_lowercase       :	Dict				):



    """simple docstring"""



    _UpperCamelCase:  List[Any]    						=			dqa_pipeline(_lowercase		,	top_k=2				)
    self.assertEqual(
        _lowercase		,	[
            [
                {'''score''': ANY(_lowercase				), '''answer''': ANY(_lowercase				), '''start''': ANY(_lowercase				), '''end''': ANY(_lowercase				)},
                {'''score''': ANY(_lowercase				), '''answer''': ANY(_lowercase				), '''start''': ANY(_lowercase				), '''end''': ANY(_lowercase				)},
            ]
        ]
        * 3		,	)



   @require_torch
   @require_detectrona
   @require_pytesseract
   def 	lowerCAmelCase    (						self       :	Union[str, Any]				):



    """simple docstring"""



    _UpperCamelCase:  Optional[int]    						=			pipeline('''document-question-answering'''		,	model='''hf-internal-testing/tiny-random-layoutlmv2'''				)
    _UpperCamelCase:  Tuple    						=			INVOICE_URL
    _UpperCamelCase:  List[str]    						=			'''How many cats are there?'''

    _UpperCamelCase:  List[Any]    						=			[
        {'''score''': 0.0001, '''answer''': '''oy 2312/2019''', '''start''': 38, '''end''': 39},
        {'''score''': 0.0001, '''answer''': '''oy 2312/2019 DUE''', '''start''': 38, '''end''': 40},
    ]
    _UpperCamelCase:  Tuple    						=			dqa_pipeline(image=_lowercase		,	question=_lowercase		,	top_k=2				)
    self.assertEqual(nested_simplify(_lowercase		,	decimals=4				)		,	_lowercase				)

    _UpperCamelCase:  Union[str, Any]    						=			dqa_pipeline({'''image''': image, '''question''': question}		,	top_k=2				)
    self.assertEqual(nested_simplify(_lowercase		,	decimals=4				)		,	_lowercase				)

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

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



   @slow
   @require_torch
   @require_detectrona
   @require_pytesseract
   def 	lowerCAmelCase    (						self       :	Tuple				):



    """simple docstring"""



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

    _UpperCamelCase:  str    						=			dqa_pipeline(image=_lowercase		,	question=_lowercase		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.9944, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.0009, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
        ]		,	)

    _UpperCamelCase:  Any    						=			dqa_pipeline({'''image''': image, '''question''': question}		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.9944, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.0009, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
        ]		,	)

    _UpperCamelCase:  Optional[int]    						=			dqa_pipeline(
        [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            [
                {'''score''': 0.9944, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
                {'''score''': 0.0009, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            ],
        ]
        * 2		,	)



   @slow
   @require_torch
   @require_detectrona
   @require_pytesseract
   def 	lowerCAmelCase    (						self       :	Any				):



    """simple docstring"""



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

    _UpperCamelCase:  List[Any]    						=			dqa_pipeline(image=_lowercase		,	question=_lowercase		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.9974, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
            {'''score''': 0.9948, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
        ]		,	)

    _UpperCamelCase:  Union[str, Any]    						=			dqa_pipeline({'''image''': image, '''question''': question}		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.9974, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
            {'''score''': 0.9948, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
        ]		,	)

    _UpperCamelCase:  Optional[Any]    						=			dqa_pipeline(
        [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            [
                {'''score''': 0.9974, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
                {'''score''': 0.9948, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            ]
        ]
        * 2		,	)



   @slow
   @require_torch
   @require_pytesseract
   @require_vision
   def 	lowerCAmelCase    (						self       :	Union[str, Any]				):



    """simple docstring"""



    _UpperCamelCase:  Tuple    						=			AutoTokenizer.from_pretrained(
        '''impira/layoutlm-document-qa'''		,	revision='''3dc6de3'''		,	add_prefix_space=_lowercase				)
    _UpperCamelCase:  Union[str, Any]    						=			pipeline(
        '''document-question-answering'''		,	model='''impira/layoutlm-document-qa'''		,	tokenizer=_lowercase		,	revision='''3dc6de3'''		,	)
    _UpperCamelCase:  Optional[int]    						=			INVOICE_URL
    _UpperCamelCase:  Optional[Any]    						=			'''What is the invoice number?'''

    _UpperCamelCase:  List[str]    						=			dqa_pipeline(image=_lowercase		,	question=_lowercase		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.4251, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.0819, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
        ]		,	)

    _UpperCamelCase:  Dict    						=			dqa_pipeline({'''image''': image, '''question''': question}		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.4251, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.0819, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
        ]		,	)

    _UpperCamelCase:  Union[str, Any]    						=			dqa_pipeline(
        [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            [
                {'''score''': 0.4251, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
                {'''score''': 0.0819, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
            ]
        ]
        * 2		,	)

    _UpperCamelCase:  List[str]    						=			list(zip(*apply_tesseract(load_image(_lowercase				)		,	_lowercase		,	''''''				)				)				)

    # This model should also work if `image` is set to None
    _UpperCamelCase:  int    						=			dqa_pipeline({'''image''': None, '''word_boxes''': word_boxes, '''question''': question}		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.4251, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.0819, '''answer''': '''1110212019''', '''start''': 23, '''end''': 23},
        ]		,	)



   @slow
   @require_torch
   @require_pytesseract
   @require_vision
   def 	lowerCAmelCase    (						self       :	int				):



    """simple docstring"""



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

    _UpperCamelCase:  List[Any]    						=			dqa_pipeline(image=_lowercase		,	question=_lowercase		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.9999, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.9998, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
        ]		,	)

    _UpperCamelCase:  str    						=			dqa_pipeline(
        [{'''image''': image, '''question''': question}, {'''image''': image, '''question''': question}]		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            [
                {'''score''': 0.9999, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
                {'''score''': 0.9998, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            ]
        ]
        * 2		,	)

    _UpperCamelCase:  Dict    						=			list(zip(*apply_tesseract(load_image(_lowercase				)		,	_lowercase		,	''''''				)				)				)

    # This model should also work if `image` is set to None
    _UpperCamelCase:  Tuple    						=			dqa_pipeline({'''image''': None, '''word_boxes''': word_boxes, '''question''': question}		,	top_k=2				)
    self.assertEqual(
        nested_simplify(_lowercase		,	decimals=4				)		,	[
            {'''score''': 0.9999, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
            {'''score''': 0.9998, '''answer''': '''us-001''', '''start''': 16, '''end''': 16},
        ]		,	)



   @slow
   @require_torch
   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    _UpperCamelCase:  Dict    						=			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'''		,	)

    _UpperCamelCase:  Dict    						=			INVOICE_URL
    _UpperCamelCase:  Any    						=			'''What is the invoice number?'''
    _UpperCamelCase:  List[Any]    						=			dqa_pipeline(image=_lowercase		,	question=_lowercase		,	top_k=2				)
    self.assertEqual(nested_simplify(_lowercase		,	decimals=4				)		,	[{'''answer''': '''us-001'''}]				)



   @require_tf
   @unittest.skip('''Document question answering not implemented in TF'''				)
   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    pass
import random




def    lowerCAmelCase_  (		lowercase:				int	,       lowercase:				float	,       lowercase:				bool = False		)     ->					dict:







 '''simple docstring'''
 _UpperCamelCase:  dict    						=			{i: [] for i in range(lowercase		)}

 # if probability is greater or equal than 1, then generate a complete graph
 if probability >= 1:
  return complete_graph(lowercase		)
 # if probability is lower or equal than 0, then return a graph without edges
 if probability <= 0:
  return graph

 # for each couple of nodes, add an edge from u to v
 # if the number randomly generated is greater than probability probability
 for i in range(lowercase		):
  for j in range(i + 1	,       lowercase		):
   if random.random() < probability:
    graph[i].append(lowercase		)
    if not directed:
     # if the graph is undirected, add an edge in from j to i, either
     graph[j].append(lowercase		)
 return graph




def    lowerCAmelCase_  (		lowercase:				int		)     ->					dict:







 '''simple docstring'''
 return {
     i: [j for j in range(lowercase		) if i != j] for i in range(lowercase		)
 }


if __name__ == "__main__":
  import doctest

  doctest.testmod()