def METHOD_NAME(self):
    # Initialize image_processing
    image_processing = self.image_processing_class(**self.image_processor_dict)
    # create random numpy tensors
    self.image_processor_tester.num_channels = 4
    image_inputs = self.image_processor_tester.prepare_image_inputs(equal_resolution=False, numpify=True)
    for image in image_inputs:
        self.assertIsInstance(image, np.ndarray)
    # Test not batched input
    encoded_images = image_processing(
        image_inputs[0], return_tensors="pt", input_data_format="channels_first"
    ).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))
    self.image_processor_tester.num_channels = 3