





'''simple docstring'''






from __future__ import annotations

from collections.abc import Iterator
from typing import Generic, TypeVar

A__    :       Any              =TypeVar('''T''')




class 			UpperCAmelCase					(      Generic[T]       ):




      def __init__(      self      :			Optional[int]      ,      __snake_case      :			T  )    ->				Dict:
            _lowerCAmelCase												=							data
            _lowerCAmelCase												=							None




      def __str__(      self      :			List[Any]  )    ->				str:
            return f"{self.data}"




class 			UpperCAmelCase					(      Generic[T]       ):




      def __init__(      self      :			Dict  )    ->				None:
            _lowerCAmelCase												=							None




      def __iter__(      self      :			int  )    ->				Iterator[T]:
            _lowerCAmelCase												=							self.top
            while node:
                  yield node.data
                  _lowerCAmelCase												=							node.next




      def __str__(      self      :			Union[str, Any]  )    ->				str:
            return "->".join([str(__snake_case  ) for item in self]  )




      def __len__(      self      :			Dict  )    ->				int:
            return len(tuple(iter(self  )  )  )




      def     lowercase__   (      self      :			List[Any]  )    ->				bool:
            return self.top is None




      def     lowercase__   (      self      :			List[Any]      ,      __snake_case      :			T  )    ->				None:
            _lowerCAmelCase												=							Node(__snake_case  )
            if not self.is_empty():
                  _lowerCAmelCase												=							self.top
            _lowerCAmelCase												=							node




      def     lowercase__   (      self      :			Optional[int]  )    ->				T:
            if self.is_empty():
                  raise IndexError("""pop from empty stack"""  )
            assert isinstance(self.top      ,      __snake_case  )
            _lowerCAmelCase												=							self.top
            _lowerCAmelCase												=							self.top.next
            return pop_node.data




      def     lowercase__   (      self      :			List[str]  )    ->				T:
            if self.is_empty():
                  raise IndexError("""peek from empty stack"""  )

            assert self.top is not None
            return self.top.data




      def     lowercase__   (      self      :			str  )    ->				None:
            _lowerCAmelCase												=							None


if __name__ == "__main__":
      from doctest import testmod

      testmod()













'''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 			UpperCAmelCase					:




            @staticmethod
            def     lowercase__   (      *__snake_case      :			Optional[Any]      ,      **__snake_case      :			Any  )    ->				Tuple:
                  pass




@is_pipeline_test
@require_torch
@require_vision
class 			UpperCAmelCase					(      unittest.TestCase       ):
      _lowercase:      Union[str, Any]											=       MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING




      def     lowercase__   (      self      :			List[str]      ,      __snake_case      :			Optional[Any]      ,      __snake_case      :			str      ,      __snake_case      :			List[str]  )    ->				int:
            _lowerCAmelCase												=							pipeline("""visual-question-answering"""      ,      model="""hf-internal-testing/tiny-vilt-random-vqa"""  )
            _lowerCAmelCase												=							[
                {
                    """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     lowercase__   (      self      :			Any      ,      __snake_case      :			List[Any]      ,      __snake_case      :			List[Any]  )    ->				Union[str, Any]:
            _lowerCAmelCase												=							vqa_pipeline(__snake_case      ,      top_k=1  )
            self.assertEqual(
                __snake_case      ,      [
                    [{"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}],
                    [{"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}],
                ]      ,      )




      @require_torch
      def     lowercase__   (      self      :			str  )    ->				int:
            _lowerCAmelCase												=							pipeline("""visual-question-answering"""      ,      model="""hf-internal-testing/tiny-vilt-random-vqa"""  )
            _lowerCAmelCase												=							"""./tests/fixtures/tests_samples/COCO/000000039769.png"""
            _lowerCAmelCase												=							"""How many cats are there?"""

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

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




      @slow
      @require_torch
      def     lowercase__   (      self      :			List[Any]  )    ->				List[str]:
            _lowerCAmelCase												=							pipeline("""visual-question-answering"""      ,      model="""dandelin/vilt-b32-finetuned-vqa"""  )
            _lowerCAmelCase												=							"""./tests/fixtures/tests_samples/COCO/000000039769.png"""
            _lowerCAmelCase												=							"""How many cats are there?"""

            _lowerCAmelCase												=							vqa_pipeline(image=__snake_case      ,      question=__snake_case      ,      top_k=2  )
            self.assertEqual(
                nested_simplify(__snake_case      ,      decimals=4  )      ,      [{"""score""": 0.87_99, """answer""": """2"""}, {"""score""": 0.2_96, """answer""": """1"""}]  )

            _lowerCAmelCase												=							vqa_pipeline({"""image""": image, """question""": question}      ,      top_k=2  )
            self.assertEqual(
                nested_simplify(__snake_case      ,      decimals=4  )      ,      [{"""score""": 0.87_99, """answer""": """2"""}, {"""score""": 0.2_96, """answer""": """1"""}]  )

            _lowerCAmelCase												=							vqa_pipeline(
                [{"""image""": image, """question""": question}, {"""image""": image, """question""": question}]      ,      top_k=2  )
            self.assertEqual(
                nested_simplify(__snake_case      ,      decimals=4  )      ,      [[{"""score""": 0.87_99, """answer""": """2"""}, {"""score""": 0.2_96, """answer""": """1"""}]] * 2      ,      )




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






