




'''simple docstring'''


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding

class 			A    (		_a    ):
							lowercase_							=				['image_processor', 'tokenizer']
							lowercase_							=				'EfficientNetImageProcessor'
							lowercase_							=				('BertTokenizer', 'BertTokenizerFast')







							def __init__(  self       :  Optional[Any]							,			lowerCAmelCase_       :  Any							,			lowerCAmelCase_       :  str					)			->							str:


														"""simple docstring"""


														super().__init__(lowerCAmelCase_							,			lowerCAmelCase_					)







							def __call__(  self       :  Any							,			lowerCAmelCase_       :  Union[str, Any]=None							,			lowerCAmelCase_       :  List[Any]=None							,			lowerCAmelCase_       :  Tuple="max_length"							,			lowerCAmelCase_       :  int=64							,			lowerCAmelCase_       :  str=None							,			**lowerCAmelCase_       :  str					)			->							Dict:


														"""simple docstring"""


														if text is None and images is None:
																					raise ValueError('''You have to specify either text or images. Both cannot be none.'''					)

														if text is not None:
																					_a	     =				self.tokenizer(
																					    lowerCAmelCase_							,			padding=lowerCAmelCase_							,			max_length=lowerCAmelCase_							,			return_tensors=lowerCAmelCase_							,			**lowerCAmelCase_					)

														if images is not None:
																					_a	     =				self.image_processor(lowerCAmelCase_							,			return_tensors=lowerCAmelCase_							,			**lowerCAmelCase_					)

														if text is not None and images is not None:
																					_a	     =				image_features.pixel_values
																					return encoding
														elif text is not None:
																					return encoding
														else:
																					return BatchEncoding(data=dict(**lowerCAmelCase_					)							,			tensor_type=lowerCAmelCase_					)







							def    __lowerCAmelCase			(  self       :  str							,			*lowerCAmelCase_       :  Union[str, Any]							,			**lowerCAmelCase_       :  int					)			->							Any:


														"""simple docstring"""


														return self.tokenizer.batch_decode(*lowerCAmelCase_							,			**lowerCAmelCase_					)







							def    __lowerCAmelCase			(  self       :  Dict							,			*lowerCAmelCase_       :  Tuple							,			**lowerCAmelCase_       :  List[str]					)			->							Optional[Any]:


														"""simple docstring"""


														return self.tokenizer.decode(*lowerCAmelCase_							,			**lowerCAmelCase_					)







							@property
							def    __lowerCAmelCase			(  self       :  Optional[int]					)			->							Any:


														"""simple docstring"""


														_a	     =				self.tokenizer.model_input_names
														_a	     =				self.image_processor.model_input_names
														return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names					)					)







'''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 			A    (		unittest.TestCase     ,_a    ):







							def    __lowerCAmelCase			(  self       :  Optional[int]					)			->							Optional[int]:


														"""simple docstring"""


														_a	     =				load_tool('''image-question-answering'''					)
														self.tool.setup()
														_a	     =				load_tool('''image-question-answering'''							,			remote=lowerCAmelCase_					)







							def    __lowerCAmelCase			(  self       :  Tuple					)			->							Optional[int]:


														"""simple docstring"""


														_a	     =				Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''					)					) / '''000000039769.png'''					)
														_a	     =				self.tool(lowerCAmelCase_							,			'''How many cats are sleeping on the couch?'''					)
														self.assertEqual(lowerCAmelCase_							,			'''2'''					)







							def    __lowerCAmelCase			(  self       :  List[str]					)			->							Union[str, Any]:


														"""simple docstring"""


														_a	     =				Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''					)					) / '''000000039769.png'''					)
														_a	     =				self.remote_tool(lowerCAmelCase_							,			'''How many cats are sleeping on the couch?'''					)
														self.assertEqual(lowerCAmelCase_							,			'''2'''					)







							def    __lowerCAmelCase			(  self       :  Dict					)			->							Tuple:


														"""simple docstring"""


														_a	     =				Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''					)					) / '''000000039769.png'''					)
														_a	     =				self.tool(image=lowerCAmelCase_							,			question='''How many cats are sleeping on the couch?'''					)
														self.assertEqual(lowerCAmelCase_							,			'''2'''					)







							def    __lowerCAmelCase			(  self       :  Tuple					)			->							Dict:


														"""simple docstring"""


														_a	     =				Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''					)					) / '''000000039769.png'''					)
														_a	     =				self.remote_tool(image=lowerCAmelCase_							,			question='''How many cats are sleeping on the couch?'''					)
														self.assertEqual(lowerCAmelCase_							,			'''2'''					)

