Does it matter if you add the same parameter multiple times to the vector of parameters in an optimiser? Example:
std::vector<torch::Tensor> differentiable_nodes;

differentiable_nodes.emplace_back(some_node.parameters()[0]);
differentiable_nodes.emplace_back(some_node.parameters()[0]);

torch::optim::SGD optimizer(differentiable_nodes, 0.001);

Does this in any way affect the training of these parameters? I want to avoid checking for duplicate nodes.