Hi @James_Trueb
these transforms are ment to be applied to datasets. For example have a look at the MNIST 10 example. You will find this line,
auto test_dataset = torch::data::datasets::MNIST(
                        kDataRoot, torch::data::datasets::MNIST::Mode::kTest)
                        .map(torch::data::transforms::Normalize<>(0.1307, 0.3081))
                        .map(torch::data::transforms::Stack<>());

What it internally does is simple. It subtracts the mean and divides by the standard deviation. So what you may be looking for is something like
for (auto& t : inputs) {
	t = t.toTensor().sub(0.5).div(0.5);
}

Can you tell me more about X_vec? What datatype has it?