

'''simple docstring'''

import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
						from PIL import Image







class lowerCamelCase   (    unittest.TestCase				,				__lowerCAmelCase				):

				def 					_lowerCamelCase    (       self )    ->							Dict:
					snake_case							=					load_tool('image-question-answering' )
					self.tool.setup()
					snake_case							=					load_tool('image-question-answering',						remote=lowercase_ )

				def 					_lowerCamelCase    (       self )    ->							Any:
					snake_case							=					Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
					snake_case							=					self.tool(lowercase_,						'How many cats are sleeping on the couch?' )
					self.assertEqual(lowercase_,						'2' )

				def 					_lowerCamelCase    (       self )    ->							Optional[int]:
					snake_case							=					Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
					snake_case							=					self.remote_tool(lowercase_,						'How many cats are sleeping on the couch?' )
					self.assertEqual(lowercase_,						'2' )

				def 					_lowerCamelCase    (       self )    ->							List[str]:
					snake_case							=					Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
					snake_case							=					self.tool(image=lowercase_,						question='How many cats are sleeping on the couch?' )
					self.assertEqual(lowercase_,						'2' )






				def 					_lowerCamelCase    (       self )    ->							str:
					snake_case							=					Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
					snake_case							=					self.remote_tool(image=lowercase_,						question='How many cats are sleeping on the couch?' )
					self.assertEqual(lowercase_,						'2' )








'''simple docstring'''

lowerCAmelCase_     =      "\n# Installation de Transformers\n! pip install transformers datasets\n# Pour installer à partir du code source au lieu de la dernière version, commentez la commande ci-dessus et décommentez la suivante.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

lowerCAmelCase_     =      [{"type": "code", "content": INSTALL_CONTENT}]
lowerCAmelCase_     =      {
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}





