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Ever wondered how PyTorch actually handles backpropagation?It builds a computational graph. Every operation you write, every multiply, every add, gets recorded as a node. Then it walks backward through that graph, applying the chain rule at every step.That's autograd. Most people treat it like magic. They call loss.backward() and move on.Read more here on TensorTonic:
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