


"""simple docstring"""
import unittest

from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
				from PIL import Image
else:





				class      __A     :





											'''simple docstring'''

											@staticmethod
											def 		lowerCAmelCase       (				*UpperCAmelCase_							:      Tuple		,       **UpperCAmelCase_							:      Optional[int]       )					->Union[str, Any]:



																		"""simple docstring"""



																		pass





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





							'''simple docstring'''

							__lowercase:		List[Any]							      =    MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING



							def 		lowerCAmelCase       (				self							:      Optional[int]		,       UpperCAmelCase_							:      Tuple		,       UpperCAmelCase_							:      int		,       UpperCAmelCase_							:      Optional[Any]       )					->Any:



														"""simple docstring"""



														snake_case_           =		pipeline("""visual-question-answering"""		,       model="""hf-internal-testing/tiny-vilt-random-vqa"""       )
														snake_case_           =		[
														    {
														        """image""": Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""       ),
														        """question""": """How many cats are there?""",
														    },
														    {
														        """image""": """./tests/fixtures/tests_samples/COCO/000000039769.png""",
														        """question""": """How many cats are there?""",
														    },
														]
														return vqa_pipeline, examples



							def 		lowerCAmelCase       (				self							:      int		,       UpperCAmelCase_							:      List[Any]		,       UpperCAmelCase_							:      int       )					->Tuple:



														"""simple docstring"""



														snake_case_           =		vqa_pipeline(UpperCAmelCase_		,       top_k=1       )
														self.assertEqual(
														    UpperCAmelCase_		,       [
														        [{"""score""": ANY(UpperCAmelCase_       ), """answer""": ANY(UpperCAmelCase_       )}],
														        [{"""score""": ANY(UpperCAmelCase_       ), """answer""": ANY(UpperCAmelCase_       )}],
														    ]		,       )



							@require_torch
							def 		lowerCAmelCase       (				self							:      Union[str, Any]       )					->Dict:



														"""simple docstring"""



														snake_case_           =		pipeline("""visual-question-answering"""		,       model="""hf-internal-testing/tiny-vilt-random-vqa"""       )
														snake_case_           =		"""./tests/fixtures/tests_samples/COCO/000000039769.png"""
														snake_case_           =		"""How many cats are there?"""

														snake_case_           =		vqa_pipeline(image=UpperCAmelCase_		,       question="""How many cats are there?"""		,       top_k=2       )
														self.assertEqual(
														    UpperCAmelCase_		,       [{"""score""": ANY(UpperCAmelCase_       ), """answer""": ANY(UpperCAmelCase_       )}, {"""score""": ANY(UpperCAmelCase_       ), """answer""": ANY(UpperCAmelCase_       )}]       )

														snake_case_           =		vqa_pipeline({"""image""": image, """question""": question}		,       top_k=2       )
														self.assertEqual(
														    UpperCAmelCase_		,       [{"""score""": ANY(UpperCAmelCase_       ), """answer""": ANY(UpperCAmelCase_       )}, {"""score""": ANY(UpperCAmelCase_       ), """answer""": ANY(UpperCAmelCase_       )}]       )



							@slow
							@require_torch
							def 		lowerCAmelCase       (				self							:      Union[str, Any]       )					->int:



														"""simple docstring"""



														snake_case_           =		pipeline("""visual-question-answering"""		,       model="""dandelin/vilt-b32-finetuned-vqa"""       )
														snake_case_           =		"""./tests/fixtures/tests_samples/COCO/000000039769.png"""
														snake_case_           =		"""How many cats are there?"""

														snake_case_           =		vqa_pipeline(image=UpperCAmelCase_		,       question=UpperCAmelCase_		,       top_k=2       )
														self.assertEqual(
														    nested_simplify(UpperCAmelCase_		,       decimals=4       )		,       [{"""score""": 0.8_799, """answer""": """2"""}, {"""score""": 0.296, """answer""": """1"""}]       )

														snake_case_           =		vqa_pipeline({"""image""": image, """question""": question}		,       top_k=2       )
														self.assertEqual(
														    nested_simplify(UpperCAmelCase_		,       decimals=4       )		,       [{"""score""": 0.8_799, """answer""": """2"""}, {"""score""": 0.296, """answer""": """1"""}]       )

														snake_case_           =		vqa_pipeline(
														    [{"""image""": image, """question""": question}, {"""image""": image, """question""": question}]		,       top_k=2       )
														self.assertEqual(
														    nested_simplify(UpperCAmelCase_		,       decimals=4       )		,       [[{"""score""": 0.8_799, """answer""": """2"""}, {"""score""": 0.296, """answer""": """1"""}]] * 2		,       )



							@require_tf
							@unittest.skip("""Visual question answering not implemented in TF"""       )
							def 		lowerCAmelCase       (				self							:      List[str]       )					->Union[str, Any]:



														"""simple docstring"""



														pass







"""simple docstring"""
__SCREAMING_SNAKE_CASE							:    str		=    'Input must be a string of 8 numbers plus letter'
__SCREAMING_SNAKE_CASE							:    Dict		=    'TRWAGMYFPDXBNJZSQVHLCKE'







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				bool:

							if not isinstance(_SCREAMING_SNAKE_CASE				, _SCREAMING_SNAKE_CASE				):
														snake_case_           =		f"""Expected string as input, found {type(_SCREAMING_SNAKE_CASE				).__name__}"""
														raise TypeError(_SCREAMING_SNAKE_CASE				)

							snake_case_           =		spanish_id.replace("""-"""				, """"""				).upper()
							if len(_SCREAMING_SNAKE_CASE				) != 9:
														raise ValueError(_SCREAMING_SNAKE_CASE				)

							try:
														snake_case_           =		int(spanish_id_clean[0:8]				)
														snake_case_           =		spanish_id_clean[8]
							except ValueError as ex:
														raise ValueError(_SCREAMING_SNAKE_CASE				) from ex

							if letter.isdigit():
														raise ValueError(_SCREAMING_SNAKE_CASE				)

							return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
				import doctest

				doctest.testmod()



