'''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 		SCREAMING_SNAKE_CASE     :







							'''simple docstring'''





							@staticmethod
							def  snake_case__				(						*lowercase__					:						Union[str, Any]       ,		**lowercase__					:						Union[str, Any]					)							->Tuple:


													'''simple docstring'''




													pass





			def 						__A							(     UpperCAmelCase					)     ->			str:




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




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







				'''simple docstring'''
				UpperCAmelCase__							=							MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING





				@require_pytesseract
				@require_vision
				def  snake_case__				(						self					:						Any       ,		lowercase__					:						Dict       ,		lowercase__					:						Dict       ,		lowercase__					:						Optional[int]					)							->Optional[int]:


										'''simple docstring'''




										_UpperCamelCase			:			List[Any]   			=						pipeline(
										    "document-question-answering"       ,		model=lowercase__       ,		tokenizer=lowercase__       ,		image_processor=lowercase__					)

										_UpperCamelCase			:			Optional[int]   			=						INVOICE_URL
										_UpperCamelCase			:			List[Any]   			=						list(zip(*apply_tesseract(load_image(lowercase__					)       ,		lowercase__       ,		""					)					)					)
										_UpperCamelCase			:			Optional[int]   			=						"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  snake_case__				(						self					:						int       ,		lowercase__					:						str       ,		lowercase__					:						Optional[int]					)							->Dict:


										'''simple docstring'''




										_UpperCamelCase			:			Optional[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  snake_case__				(						self					:						int					)							->Union[str, Any]:


										'''simple docstring'''




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

										_UpperCamelCase			:			str   			=						[
										    {"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},
										]
										_UpperCamelCase			:			Tuple   			=						dqa_pipeline(image=lowercase__       ,		question=lowercase__       ,		top_k=2					)
										self.assertEqual(nested_simplify(lowercase__       ,		decimals=4					)       ,		lowercase__					)

										_UpperCamelCase			:			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			:			Optional[Any]   			=						"./tests/fixtures/tests_samples/COCO/000000039769.png"
										_UpperCamelCase			:			List[str]   			=						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			:			List[str]   			=						[]
										_UpperCamelCase			:			Optional[int]   			=						[]
										_UpperCamelCase			:			Union[str, 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  snake_case__				(						self					:						str					)							->Any:


										'''simple docstring'''




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

										_UpperCamelCase			:			Optional[int]   			=						dqa_pipeline(image=lowercase__       ,		question=lowercase__       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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},
										    ]       ,		)

										_UpperCamelCase			:			int   			=						dqa_pipeline({"image": image, "question": question}       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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},
										    ]       ,		)

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


										'''simple docstring'''




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

										_UpperCamelCase			:			Any   			=						dqa_pipeline(image=lowercase__       ,		question=lowercase__       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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},
										    ]       ,		)

										_UpperCamelCase			:			List[str]   			=						dqa_pipeline({"image": image, "question": question}       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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},
										    ]       ,		)

										_UpperCamelCase			:			List[Any]   			=						dqa_pipeline(
										    [{"image": image, "question": question}, {"image": image, "question": question}]       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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  snake_case__				(						self					:						Optional[Any]					)							->Optional[int]:


										'''simple docstring'''




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

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

										_UpperCamelCase			:			List[str]   			=						dqa_pipeline({"image": image, "question": question}       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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},
										    ]       ,		)

										_UpperCamelCase			:			Optional[int]   			=						dqa_pipeline(
										    [{"image": image, "question": question}, {"image": image, "question": question}]       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		decimals=4					)       ,		[
										        [
										            {"score": 0.4_2_5_1, "answer": "us-001", "start": 16, "end": 16},
										            {"score": 0.0_8_1_9, "answer": "1110212019", "start": 23, "end": 23},
										        ]
										    ]
										    * 2       ,		)

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

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


										'''simple docstring'''




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

										_UpperCamelCase			:			Dict   			=						dqa_pipeline(image=lowercase__       ,		question=lowercase__       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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},
										    ]       ,		)

										_UpperCamelCase			:			int   			=						dqa_pipeline(
										    [{"image": image, "question": question}, {"image": image, "question": question}]       ,		top_k=2					)
										self.assertEqual(
										    nested_simplify(lowercase__       ,		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       ,		)

										_UpperCamelCase			:			List[str]   			=						list(zip(*apply_tesseract(load_image(lowercase__					)       ,		lowercase__       ,		""					)					)					)

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


										'''simple docstring'''




										_UpperCamelCase			:			Optional[Any]   			=						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			:			int   			=						INVOICE_URL
										_UpperCamelCase			:			int   			=						"What is the invoice number?"
										_UpperCamelCase			:			str   			=						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  snake_case__				(						self					:						Optional[int]					)							->str:


										'''simple docstring'''




										pass



'''simple docstring'''





from __future__ import annotations

from cmath import sqrt
def 						__A							(     UpperCAmelCase     ,UpperCAmelCase     ,UpperCAmelCase					)     ->			tuple[complex, complex]:




						'''simple docstring'''

						if a == 0:
												raise ValueError("Coefficient 'a' must not be zero."					)
						_UpperCamelCase			:			List[str]   			=						b * b - 4 * a * c

						_UpperCamelCase			:			Dict   			=						(-b + sqrt(UpperCAmelCase					)) / (2 * a)
						_UpperCamelCase			:			Optional[int]   			=						(-b - sqrt(UpperCAmelCase					)) / (2 * a)

						return (
						    root_a.real if not root_a.imag else root_a,
						    root_a.real if not root_a.imag else root_a,
						)
def 						__A							(     )     ->			List[Any]:




						'''simple docstring'''
						_UpperCamelCase			,       _UpperCamelCase			:			Any   			=						quadratic_roots(a=5     ,b=6     ,c=1					)
						print(f'''The solutions are: {solutiona} and {solutiona}'''					)


if __name__ == "__main__":
			main()


