feature/recompute #422
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feature/recompute #422
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…r time just like ZeRO stages, as we recompute more and more of the model in the future possibly. and make it default on because it is awesome
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Option to recompute forward activations during backward pass.
Will be an int so that 0 = don't be fancy, 1,2,3,4... (in the future) recompute more and more.
This trades off VRAM for latency of a single fwd/bwd pass, because we do more calculations, but we save less in memory.
The big upside is that the VRAM savings mean you can crank up the batch size, and can actually end up with a net win on the tokens throughput during training.
For example on my A100 40GB, with -r 0 I can only fit batch size 10 for the biggest GPT-2 model. But with -r 1 (recompute GeLU) I can fit batch size 12, and a net win of token throughput because of that.