For implementers, the locking model adds a fair amount of non-trivial internal bookkeeping. Every operation must check lock state, readers must be tracked, and the interplay between locks, cancellation, and error states creates a matrix of edge cases that must all be handled correctly.
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Implication: The ANE hardware likely has a small set of fixed compute primitives (convolution, matrix multiply, elementwise) that are parameterized by tensor shape descriptors. The E5 binary describes which primitives to chain and how to connect them, not the compute itself.