# JAX provides the device arrays returned by apply(). The [cuda13] variant
# bundles its own CUDA pip wheels, so it runs on the default Debian base image.
# Unlike CuPy/PyTorch, JAX's plugin registers against the host GPU driver (CUDA
# 13 on the CI runners), not the CUDA runtime it ships: the [cuda12] plugin fails
# to register under a CUDA 13 driver ("Unknown backend cuda") and silently falls
# back to CPU, so both matrix legs use cuda13 here (see the sibling
# tesseract_requirements_cuda13.txt). JAX exposes device buffers only via DLPack,
# the path this example exercises.
jax[cuda13]
