def test_non_batch_inp(self, device, dtype) -> None:
        """Here we test if we can handle non-batched inputs (input image, JPEG quality, and QT's)."""
        H, W = 32, 32
        img = torch.rand(3, H, W, device=device, dtype=dtype)
        jpeg_quality = torch.randint(low=0, high=100, size=(1,), device=device, dtype=dtype)
        qt_y = torch.randint(low=1, high=255, size=(8, 8), device=device, dtype=dtype)
        qt_c = torch.randint(low=1, high=255, size=(8, 8), device=device, dtype=dtype)
        img_jpeg = kornia.enhance.jpeg_codec_differentiable(img, jpeg_quality, qt_y, qt_c)
        assert img_jpeg is not None
        assert img_jpeg.shape == img.shape
Here we test if we can handle non-batched inputs (input image, JPEG quality, and QT's).
tests/enhance/test_jpeg.py