





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   __lowerCAmelCase			:





     @staticmethod
     def 	_snake_case ( *snake_case					,			**snake_case      )				->  int:
        """simple docstring"""





        pass







@is_pipeline_test
@require_torch
@require_vision
class   __lowerCAmelCase			(					unittest.TestCase  ):
   _UpperCamelCase :						Optional[int]     		=				MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING





   def 	_snake_case ( self					,			snake_case					,			snake_case					,			snake_case      )				->  List[Any]:
      """simple docstring"""





      a__	:						Tuple      		=  pipeline("visual-question-answering"					,			model="hf-internal-testing/tiny-vilt-random-vqa"      )
      a__	:						Dict      		=  [
          {
              "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 	_snake_case ( self					,			snake_case					,			snake_case      )				->  Tuple:
      """simple docstring"""





      a__	:						int      		=  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 	_snake_case ( self      )				->  Optional[int]:
      """simple docstring"""





      a__	:						int      		=  pipeline("visual-question-answering"					,			model="hf-internal-testing/tiny-vilt-random-vqa"      )
      a__	:						Union[str, Any]      		=  "./tests/fixtures/tests_samples/COCO/000000039769.png"
      a__	:						Any      		=  "How many cats are there?"

      a__	:						Any      		=  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      )}]      )

      a__	:						Optional[int]      		=  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 	_snake_case ( self      )				->  Optional[Any]:
      """simple docstring"""





      a__	:						int      		=  pipeline("visual-question-answering"					,			model="dandelin/vilt-b32-finetuned-vqa"      )
      a__	:						Tuple      		=  "./tests/fixtures/tests_samples/COCO/000000039769.png"
      a__	:						List[str]      		=  "How many cats are there?"

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

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

      a__	:						Optional[Any]      		=  vqa_pipeline(
          [{"image": image, "question": question}, {"image": image, "question": question}]					,			top_k=2      )
      self.assertEqual(
          nested_simplify(snake_case					,			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 	_snake_case ( self      )				->  Tuple:
      """simple docstring"""





      pass








# Lint as: python3
import itertools
import os
import re


SCREAMING_SNAKE_CASE__       :			Tuple			      =						re.compile(R"""([A-Z]+)([A-Z][a-z])""")
SCREAMING_SNAKE_CASE__       :			List[str]			      =						re.compile(R"""([a-z\d])([A-Z])""")

SCREAMING_SNAKE_CASE__       :			Tuple			      =						re.compile(R"""(?<!_)_(?!_)""")
SCREAMING_SNAKE_CASE__       :			Dict			      =						re.compile(R"""(_{2,})""")

SCREAMING_SNAKE_CASE__       :			List[Any]			      =						R"""^\w+(\.\w+)*$"""

SCREAMING_SNAKE_CASE__       :			Union[str, Any]			      =						R"""<>:/\|?*"""






def       _A  (      lowerCamelCase   ):
   a__	:						List[str]      		=  _uppercase_uppercase_re.sub(r"\1_\2"							, lowerCamelCase   )
   a__	:						Dict      		=  _lowercase_uppercase_re.sub(r"\1_\2"							, lowerCamelCase   )
   return name.lower()






def       _A  (      lowerCamelCase   ):
   a__	:						Tuple      		=  _single_underscore_re.split(lowerCamelCase   )
   a__	:						Any      		=  [_multiple_underscores_re.split(lowerCamelCase   ) for n in name]
   return "".join(n.capitalize() for n in itertools.chain.from_iterable(lowerCamelCase   ) if n != ""   )






def       _A  (      lowerCamelCase   ):
   if os.path.basename(lowerCamelCase   ) != name:
      raise ValueError(F"""Should be a dataset name, not a path: {name}"""   )
   return camelcase_to_snakecase(lowerCamelCase   )






def       _A  (      lowerCamelCase							, lowerCamelCase   ):
   if os.path.basename(lowerCamelCase   ) != name:
      raise ValueError(F"""Should be a dataset name, not a path: {name}"""   )
   if not re.match(_split_re							, lowerCamelCase   ):
      raise ValueError(F"""Split name should match '{_split_re}'' but got '{split}'."""   )
   return F"""{filename_prefix_for_name(lowerCamelCase   )}-{split}"""






def       _A  (      lowerCamelCase							, lowerCamelCase							, lowerCamelCase							, lowerCamelCase=None   ):
   a__	:						Union[str, Any]      		=  filename_prefix_for_split(lowerCamelCase							, lowerCamelCase   )
   if filetype_suffix:
      prefix += F""".{filetype_suffix}"""
   a__	:						Any      		=  os.path.join(lowerCamelCase							, lowerCamelCase   )
   return F"""{filepath}*"""






def       _A  (      lowerCamelCase							, lowerCamelCase							, lowerCamelCase							, lowerCamelCase=None							, lowerCamelCase=None   ):
   a__	:						List[str]      		=  filename_prefix_for_split(lowerCamelCase							, lowerCamelCase   )
   a__	:						Tuple      		=  os.path.join(lowerCamelCase							, lowerCamelCase   )

   if shard_lengths:
      a__	:						List[str]      		=  len(lowerCamelCase   )
      a__	:						str      		=  [F"""{prefix}-{shard_id:05d}-of-{num_shards:05d}""" for shard_id in range(lowerCamelCase   )]
      if filetype_suffix:
         a__	:						Optional[Any]      		=  [filename + F""".{filetype_suffix}""" for filename in filenames]
      return filenames
   else:
      a__	:						Optional[int]      		=  prefix
      if filetype_suffix:
         filename += F""".{filetype_suffix}"""
      return [filename]

