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That would be nice for experimentation but for production use cases knowing the whole graph unlocks a number of optimizations.



This is a meme that keeps getting repeated, and I don't know why. Tensorflow, for example, despite several years of development, does basically little to no graph optimizations and for tons of tasks ends up much slower than PyTorch / Chainer / DyNet (Tensorflow is developing a "JIT compiler" but it is still in alpha).

It goes without saying that a framework that does define-by-run also knows the whole graph.




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