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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_range_vector(size: int, device: int) -> torch.Tensor: """ Returns a range vector with the desired size, starting at 0. The CUDA implementation is meant to avoid copy data from CPU to GPU. """

    if device > -1:
        return torch.cuda.LongTensor(size, device=device).fill_(1).cumsum(0) - 1
    else:
        return torch.arange(0, size, dtype=torch.long)