def get_expected_values(self, image_inputs, batched=False):
        """
        This function computes the expected height and width when providing images to BridgeTowerImageProcessor,
        assuming do_resize is set to True with a scalar size and size_divisor.
        """
        if not batched:
            size = self.size["shortest_edge"]
            image = image_inputs[0]
            if isinstance(image, Image.Image):
                w, h = image.size
            else:
                h, w = image.shape[1], image.shape[2]
            scale = size / min(w, h)
            if h < w:
                newh, neww = size, scale * w
            else:
                newh, neww = scale * h, size

            max_size = int((1333 / 800) * size)
            if max(newh, neww) > max_size:
                scale = max_size / max(newh, neww)
                newh = newh * scale
                neww = neww * scale

            newh, neww = int(newh + 0.5), int(neww + 0.5)
            expected_height, expected_width = (
                newh // self.size_divisor * self.size_divisor,
                neww // self.size_divisor * self.size_divisor,
            )

        else:
            expected_values = []
            for image in image_inputs:
                expected_height, expected_width = self.get_expected_values([image])
                expected_values.append((expected_height, expected_width))
            expected_height = max(expected_values, key=lambda item: item[0])[0]
            expected_width = max(expected_values, key=lambda item: item[1])[1]

        return expected_height, expected_width

        This function computes the expected height and width when providing images to BridgeTowerImageProcessor,
        assuming do_resize is set to True with a scalar size and size_divisor.
        
dpkd/transformers/tests/models/bridgetower/test_image_processing_bridgetower.py