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Autograd in PyTorch — How to Apply it on a Customised Function
Autograd package in PyTorch enables us to implement the gradient effectively and in a friendly manner.
Differentiation is a crucial step in nearly all deep learning optimization algorithms. Deep learning frameworks such as PyTorch make it easy to calculate the gradient effectively. It is mainly based on the computational graph, tracking which data combined through which operations to produce the output. This is possible through back-propagation procedure. Here, backpropagate simply means to trace through the computational…
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