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Introduction to Functional Automatic Differentiation Automatic differentiation is a core technique in neural network training that enables efficient computation of gradients for optimization. MindSpore implements a functional approach to automatic differentiation through its grad and value_and_grad interfaces, which provide mathematical semanti ...

Automatic differentiation (AD) computes exact derivatives efficiently by applying the chain rule during program execution. Two primary strategies exist: forward mode and reverse mode. Their suitability depends on the shape of the function being differentiated—specifically, the number of inputs versus outputs. Intuitive Analogy: Manufacturing Wo ...