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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 evaluate(tensor: BKTensor) -> TensorLike: """Return the value of a tensor"""

    if isinstance(tensor, _DTYPE):
        if torch.numel(tensor) == 1:
            return tensor.item()
        if tensor.numel() == 2:
            return tensor[0].cpu().numpy() + 1.0j * tensor[1].cpu().numpy()

        return tensor[0].cpu().numpy() + 1.0j * tensor[1].cpu().numpy()
    return tensor