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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 move_optimizer_to_cuda(optimizer):
 """ Move the optimizer state to GPU, if necessary. After calling, any parameter specific state in the optimizer will be located on the same device as the parameter. """

    for param_group in optimizer.param_groups:
        for param in param_group['params']:
            if param.is_cuda:
                param_state = optimizer.state[param]
                for k in param_state.keys():
                    if isinstance(param_state[k], torch.Tensor):
                        param_state[k] = param_state[k].cuda(device=param.get_device())