Unsupported device: cuda (device type: cuda, variant: beta)

I just built the master branch on NVIDIA Jetson Thor (Blackwell, CUDA 13.0, CUDA Arch 11.0), but I get the following issue with the version set specified below:

torch=2.9.0a0+50eac811a6.nv25.9
torchvision=0.24.0a0+98f8b375
torchcodec=0.9.0a0

Test code:

rom torchcodec.decoders import set_cuda_backend, VideoDecoder

video_file = "video.mp4"

with set_cuda_backend("beta"):  # Use the BETA backend, it's faster!
    decoder = VideoDecoder(video_file, device="cuda")

Error:

Traceback (most recent call last):
  File "/root/test_codec.py", line 6, in <module>
    decoder = VideoDecoder(video_file, device="cuda")
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/torchcodec/decoders/_video_decoder.py", line 154, in __init__
    core.add_video_stream(
  File "/usr/local/lib/python3.12/dist-packages/torch/_ops.py", line 840, in __call__
    return self._op(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Unsupported device: cuda (device type: cuda, variant: beta)

As it is already specified with RTX 5090 here https://github.com/meta-pytorch/torchcodec/issues/1006#issuecomment-3485482616, I guess it is related to Blackwell architecture. Is there any workaround to this?

Reproduce the failure with the shown VideoDecoder and set_cuda_backend("beta") example, then inspect torchcodec/decoders/_video_decoder.py around VideoDecoder and the core.add_video_stream call. Compare the behavior with the RTX 5090 discussion in issue #1006. Done means identifying whether Jetson Thor/Blackwell is unsupported and documenting a verified workaround or limitation.