
"""simple docstring"""




from typing import Any



class 			lowerCAmelCase_		:


				"""simple docstring"""



				def __init__(self     , SCREAMING_SNAKE_CASE__					)      ->	Dict:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Any     =     data
											SCREAMING_SNAKE_CASE__		: Any     =     None



				def __repr__(self					)      ->	List[Any]:



											"""simple docstring"""




											return F'''Node({self.data})'''






class 			lowerCAmelCase_		:


				"""simple docstring"""



				def __init__(self					)      ->	str:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Any     =     None



				def __iter__(self					)      ->	Any:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Any     =     self.head
											while node:
																		yield node.data
																		SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     node.next



				def __len__(self					)      ->	int:



											"""simple docstring"""




											return sum(1 for _ in self					)



				def __repr__(self					)      ->	Tuple:



											"""simple docstring"""




											return "->".join([str(__lowercase					) for item in self]					)



				def __getitem__(self     , SCREAMING_SNAKE_CASE__					)      ->	Tuple:



											"""simple docstring"""




											if not 0 <= index < len(self					):
																		raise ValueError("""list index out of range."""					)
											for i, node in enumerate(self					):
																		if i == index:
																									return node
											return None



				def __setitem__(self     , SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)      ->	Optional[Any]:



											"""simple docstring"""




											if not 0 <= index < len(self					):
																		raise ValueError("""list index out of range."""					)
											SCREAMING_SNAKE_CASE__		: List[Any]     =     self.head
											for _ in range(__lowercase					):
																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     current.next
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     data



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__					)      ->	Any:



											"""simple docstring"""




											self.insert_nth(len(self					)     , __lowercase					)



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__					)      ->	List[str]:



											"""simple docstring"""




											self.insert_nth(0     , __lowercase					)



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



											"""simple docstring"""




											if not 0 <= index <= len(self					):
																		raise IndexError("""list index out of range"""					)
											SCREAMING_SNAKE_CASE__		: Tuple     =     Node(__lowercase					)
											if self.head is None:
																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     new_node
											elif index == 0:
																		SCREAMING_SNAKE_CASE__		: List[str]     =     self.head  # link new_node to head
																		SCREAMING_SNAKE_CASE__		: str     =     new_node
											else:
																		SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     self.head
																		for _ in range(index - 1					):
																									SCREAMING_SNAKE_CASE__		: List[Any]     =     temp.next
																		SCREAMING_SNAKE_CASE__		: List[Any]     =     temp.next
																		SCREAMING_SNAKE_CASE__		: Dict     =     new_node



				def 			__magic_name__					(self					)      ->	int:  # print every node data



											"""simple docstring"""




											print(self					)



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




											return self.delete_nth(0					)



				def 			__magic_name__					(self					)      ->	str:  # delete from tail



											"""simple docstring"""




											return self.delete_nth(len(self					) - 1					)



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__ = 0					)      ->	Dict:



											"""simple docstring"""




											if not 0 <= index <= len(self					) - 1:  # test if index is valid
																		raise IndexError("""List index out of range."""					)
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     self.head  # default first node
											if index == 0:
																		SCREAMING_SNAKE_CASE__		: List[Any]     =     self.head.next
											else:
																		SCREAMING_SNAKE_CASE__		: Optional[int]     =     self.head
																		for _ in range(index - 1					):
																									SCREAMING_SNAKE_CASE__		: int     =     temp.next
																		SCREAMING_SNAKE_CASE__		: Optional[Any]     =     temp.next
																		SCREAMING_SNAKE_CASE__		: List[str]     =     temp.next.next
											return delete_node.data



				def 			__magic_name__					(self					)      ->	Optional[int]:



											"""simple docstring"""




											return self.head is None



				def 			__magic_name__					(self					)      ->	int:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     None
											SCREAMING_SNAKE_CASE__		: Optional[int]     =     self.head

											while current:
																		# Store the current node's next node.
																		SCREAMING_SNAKE_CASE__		: Any     =     current.next
																		# Make the current node's next point backwards
																		SCREAMING_SNAKE_CASE__		: str     =     prev
																		# Make the previous node be the current node
																		SCREAMING_SNAKE_CASE__		: Optional[int]     =     current
																		# Make the current node the next node (to progress iteration)
																		SCREAMING_SNAKE_CASE__		: List[Any]     =     next_node
											# Return prev in order to put the head at the end
											SCREAMING_SNAKE_CASE__		: int     =     prev






def lowercase_						(     ):
							SCREAMING_SNAKE_CASE__		: Tuple     =     LinkedList()
							assert linked_list.is_empty() is True
							assert str(SCREAMING_SNAKE_CASE_		) == ""

							try:
														linked_list.delete_head()
														raise AssertionError  # This should not happen.
							except IndexError:
														assert True  # This should happen.

							try:
														linked_list.delete_tail()
														raise AssertionError  # This should not happen.
							except IndexError:
														assert True  # This should happen.

							for i in range(10		):
														assert len(SCREAMING_SNAKE_CASE_		) == i
														linked_list.insert_nth(SCREAMING_SNAKE_CASE_     ,i + 1		)
							assert str(SCREAMING_SNAKE_CASE_		) == "->".join(str(SCREAMING_SNAKE_CASE_		) for i in range(1     ,11		)		)

							linked_list.insert_head(0		)
							linked_list.insert_tail(11		)
							assert str(SCREAMING_SNAKE_CASE_		) == "->".join(str(SCREAMING_SNAKE_CASE_		) for i in range(0     ,12		)		)

							assert linked_list.delete_head() == 0
							assert linked_list.delete_nth(9		) == 10
							assert linked_list.delete_tail() == 11
							assert len(SCREAMING_SNAKE_CASE_		) == 9
							assert str(SCREAMING_SNAKE_CASE_		) == "->".join(str(SCREAMING_SNAKE_CASE_		) for i in range(1     ,10		)		)

							assert all(linked_list[i] == i + 1 for i in range(0     ,9		)		) is True

							for i in range(0     ,9		):
														SCREAMING_SNAKE_CASE__		: List[str]     =     -i
							assert all(linked_list[i] == -i for i in range(0     ,9		)		) is True

							linked_list.reverse()
							assert str(SCREAMING_SNAKE_CASE_		) == "->".join(str(SCREAMING_SNAKE_CASE_		) for i in range(-8     ,1		)		)

def lowercase_						(     ):
							SCREAMING_SNAKE_CASE__		: List[Any]     =     [
							    -9,
							    100,
							    Node(77_345_112		),
							    """dlrow olleH""",
							    7,
							    5_555,
							    0,
							    -192.55555,
							    """Hello, world!""",
							    77.9,
							    Node(10		),
							    None,
							    None,
							    12.20,
							]
							SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     LinkedList()

							for i in test_input:
														linked_list.insert_tail(SCREAMING_SNAKE_CASE_		)

							# Check if it's empty or not
							assert linked_list.is_empty() is False
							assert (
							    str(SCREAMING_SNAKE_CASE_		) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
							    "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
							)

							# Delete the head
							SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     linked_list.delete_head()
							assert result == -9
							assert (
							    str(SCREAMING_SNAKE_CASE_		) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
							    "Hello, world!->77.9->Node(10)->None->None->12.2"
							)

							# Delete the tail
							SCREAMING_SNAKE_CASE__		: Tuple     =     linked_list.delete_tail()
							assert result == 12.2
							assert (
							    str(SCREAMING_SNAKE_CASE_		) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
							    "Hello, world!->77.9->Node(10)->None->None"
							)

							# Delete a node in specific location in linked list
							SCREAMING_SNAKE_CASE__		: List[Any]     =     linked_list.delete_nth(10		)
							assert result is None
							assert (
							    str(SCREAMING_SNAKE_CASE_		) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
							    "Hello, world!->77.9->Node(10)->None"
							)

							# Add a Node instance to its head
							linked_list.insert_head(Node("""Hello again, world!"""		)		)
							assert (
							    str(SCREAMING_SNAKE_CASE_		)
							    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
							    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
							)

							# Add None to its tail
							linked_list.insert_tail(SCREAMING_SNAKE_CASE_		)
							assert (
							    str(SCREAMING_SNAKE_CASE_		)
							    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
							    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
							)

							# Reverse the linked list
							linked_list.reverse()
							assert (
							    str(SCREAMING_SNAKE_CASE_		)
							    == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
							    "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
							)

def lowercase_						(     ):
							from doctest import testmod

							testmod()

							SCREAMING_SNAKE_CASE__		: List[Any]     =     LinkedList()
							linked_list.insert_head(input("""Inserting 1st at head """		).strip()		)
							linked_list.insert_head(input("""Inserting 2nd at head """		).strip()		)
							print("""\nPrint list:"""		)
							linked_list.print_list()
							linked_list.insert_tail(input("""\nInserting 1st at tail """		).strip()		)
							linked_list.insert_tail(input("""Inserting 2nd at tail """		).strip()		)
							print("""\nPrint list:"""		)
							linked_list.print_list()
							print("""\nDelete head"""		)
							linked_list.delete_head()
							print("""Delete tail"""		)
							linked_list.delete_tail()
							print("""\nPrint list:"""		)
							linked_list.print_list()
							print("""\nReverse linked list"""		)
							linked_list.reverse()
							print("""\nPrint list:"""		)
							linked_list.print_list()
							print("""\nString representation of linked list:"""		)
							print(SCREAMING_SNAKE_CASE_		)
							print("""\nReading/changing Node data using indexing:"""		)
							print(f'''Element at Position 1: {linked_list[1]}'''		)
							SCREAMING_SNAKE_CASE__		: List[Any]     =     input("""Enter New Value: """		).strip()
							print("""New list:"""		)
							print(SCREAMING_SNAKE_CASE_		)
							print(f'''length of linked_list is : {len(SCREAMING_SNAKE_CASE_		)}'''		)


if __name__ == "__main__":
						main()






"""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 			lowerCAmelCase_		:


									"""simple docstring"""



									@staticmethod
									def 			__magic_name__					(*SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)      ->	Union[str, Any]:



																"""simple docstring"""




																pass






					def lowercase_						(     _snake_case		):
												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__   :					str												=				(
    'https://huggingface.co/spaces/impira/docquery/resolve/2f6c96314dc84dfda62d40de9da55f2f5165d403/invoice.png'
)



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


				"""simple docstring"""



				__UpperCamelCase   :		List[Any]       =     MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING



				@require_pytesseract
				@require_vision
				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)      ->	Optional[Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: List[str]     =     pipeline(
											    """document-question-answering"""     , model=SCREAMING_SNAKE_CASE__     , tokenizer=SCREAMING_SNAKE_CASE__     , image_processor=SCREAMING_SNAKE_CASE__					)

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



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)      ->	List[Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     dqa_pipeline(SCREAMING_SNAKE_CASE__     , top_k=2					)
											self.assertEqual(
											    SCREAMING_SNAKE_CASE__     , [
											        [
											            {"""score""": ANY(SCREAMING_SNAKE_CASE__					), """answer""": ANY(SCREAMING_SNAKE_CASE__					), """start""": ANY(SCREAMING_SNAKE_CASE__					), """end""": ANY(SCREAMING_SNAKE_CASE__					)},
											            {"""score""": ANY(SCREAMING_SNAKE_CASE__					), """answer""": ANY(SCREAMING_SNAKE_CASE__					), """start""": ANY(SCREAMING_SNAKE_CASE__					), """end""": ANY(SCREAMING_SNAKE_CASE__					)},
											        ]
											    ]
											    * 3     , )



				@require_torch
				@require_detectrona
				@require_pytesseract
				def 			__magic_name__					(self					)      ->	List[Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: List[Any]     =     pipeline("""document-question-answering"""     , model="""hf-internal-testing/tiny-random-layoutlmv2"""					)
											SCREAMING_SNAKE_CASE__		: str     =     INVOICE_URL
											SCREAMING_SNAKE_CASE__		: Any     =     """How many cats are there?"""

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

											SCREAMING_SNAKE_CASE__		: str     =     dqa_pipeline({"""image""": image, """question""": question}     , top_k=2					)
											self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     , decimals=4					)     , SCREAMING_SNAKE_CASE__					)

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

											# We can optionnally pass directly the words and bounding boxes
											SCREAMING_SNAKE_CASE__		: Tuple     =     """./tests/fixtures/tests_samples/COCO/000000039769.png"""
											SCREAMING_SNAKE_CASE__		: Dict     =     []
											SCREAMING_SNAKE_CASE__		: Any     =     []
											SCREAMING_SNAKE_CASE__		: Dict     =     dqa_pipeline(image=SCREAMING_SNAKE_CASE__     , question=SCREAMING_SNAKE_CASE__     , words=SCREAMING_SNAKE_CASE__     , boxes=SCREAMING_SNAKE_CASE__     , top_k=2					)
											self.assertEqual(SCREAMING_SNAKE_CASE__     , []					)



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



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: List[str]     =     pipeline(
											    """document-question-answering"""     , model="""tiennvcs/layoutlmv2-base-uncased-finetuned-docvqa"""     , revision="""9977165"""     , )
											SCREAMING_SNAKE_CASE__		: str     =     INVOICE_URL
											SCREAMING_SNAKE_CASE__		: Optional[int]     =     """What is the invoice number?"""

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

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

											SCREAMING_SNAKE_CASE__		: Optional[int]     =     dqa_pipeline(
											    [{"""image""": image, """question""": question}, {"""image""": image, """question""": question}]     , top_k=2					)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE__     , 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 			__magic_name__					(self					)      ->	List[str]:



											"""simple docstring"""




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

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

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

											SCREAMING_SNAKE_CASE__		: List[str]     =     dqa_pipeline(
											    [{"""image""": image, """question""": question}, {"""image""": image, """question""": question}]     , top_k=2					)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE__     , 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 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




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

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

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

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

											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     list(zip(*apply_tesseract(load_image(SCREAMING_SNAKE_CASE__					)     , SCREAMING_SNAKE_CASE__     , """"""					)					)					)

											# This model should also work if `image` is set to None
											SCREAMING_SNAKE_CASE__		: Dict     =     dqa_pipeline({"""image""": None, """word_boxes""": word_boxes, """question""": question}     , top_k=2					)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE__     , 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 			__magic_name__					(self					)      ->	List[str]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Any     =     AutoTokenizer.from_pretrained(
											    """impira/layoutlm-document-qa"""     , revision="""3dc6de3"""     , add_prefix_space=SCREAMING_SNAKE_CASE__					)
											SCREAMING_SNAKE_CASE__		: Dict     =     pipeline(
											    """document-question-answering"""     , model="""impira/layoutlm-document-qa"""     , tokenizer=SCREAMING_SNAKE_CASE__     , revision="""3dc6de3"""     , max_seq_len=50     , )
											SCREAMING_SNAKE_CASE__		: str     =     INVOICE_URL
											SCREAMING_SNAKE_CASE__		: Dict     =     """What is the invoice number?"""

											SCREAMING_SNAKE_CASE__		: Optional[int]     =     dqa_pipeline(image=SCREAMING_SNAKE_CASE__     , question=SCREAMING_SNAKE_CASE__     , top_k=2					)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE__     , decimals=4					)     , [
											        {"""score""": 0.9999, """answer""": """us-001""", """start""": 16, """end""": 16},
											        {"""score""": 0.9998, """answer""": """us-001""", """start""": 16, """end""": 16},
											    ]     , )

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

											SCREAMING_SNAKE_CASE__		: Any     =     list(zip(*apply_tesseract(load_image(SCREAMING_SNAKE_CASE__					)     , SCREAMING_SNAKE_CASE__     , """"""					)					)					)

											# This model should also work if `image` is set to None
											SCREAMING_SNAKE_CASE__		: List[Any]     =     dqa_pipeline({"""image""": None, """word_boxes""": word_boxes, """question""": question}     , top_k=2					)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE__     , 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 			__magic_name__					(self					)      ->	Optional[Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     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"""     , )

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



				@require_tf
				@unittest.skip("""Document question answering not implemented in TF"""					)
				def 			__magic_name__					(self					)      ->	int:



											"""simple docstring"""




											pass




