def METHOD_NAME(self):
    # Initialize image_processing
    image_processing = self.image_processing_class(**self.image_processor_dict)
    # create random PyTorch tensors
    image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False, torchify=True)
    for image in image_inputs:
        self.assertIsInstance(image, torch.Tensor)
    # Test not batched input
    encoded_images = image_processing(image_inputs[0], return_tensors="pt").pixel_values
    expected_output_image_shape = self.image_processor_tester.expected_output_image_shape([image_inputs[0]])
    self.assertEqual(tuple(encoded_images.shape), (1, *expected_output_image_shape))