CUDA needs to default to sm_80 and use devicearrays

[powderluv]

We need model the CUDA backend in SHARK to be similar to:

https://github.com/nod-ai/transformer-benchmarks/blob/435984a420a2f285f717aa4752c14c0cabfd8c96/benchmark.py#L397-L437

    if use_gpu:
        backend = "cuda"
        backend_config = "cuda"
        args = ["--iree-cuda-llvm-target-arch=sm_80", "--iree-hal-cuda-disable-loop-nounroll-wa"]
        ireert.flags.FUNCTION_INPUT_VALIDATION = False
        ireert.flags.parse_flags("--cuda_allow_inline_execution")

...

    # Setting up input on host and moving to device.
    host_inputs =[encoded_input["input_ids"], encoded_input["attention_mask"], encoded_input["token_type_ids"]]
    if use_gpu:
        device_inputs = [ireert.asdevicearray(config.device, a) for a in host_inputs]
    else:
        device_inputs = host_inputs

[pashu123]

Added here: #52