The use_cuda parameter is only available in versions newer than 0.3.0, yes. Even then it adds some overhead. The recommended approach appears to be the emit_nvtx 238 function:
with torch.cuda.profiler.profile():
    model(x) # Warmup CUDA memory allocator and profiler
    with torch.autograd.profiler.emit_nvtx():
        model(x)