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This is a very interesting claim. I find it credible because it stands to reason that projects like DeepSpeed[1] and TorchScript[2] wouldn't need to exist if inference performance of research PyTorch models was satisfactory for production, but often case it isn't.
It appears as though FlashLight is built on ArrayFire. I haven't seen how gradients are managed in arrayfire-ml, but perhaps it is the case that the autograd implementation in PyTorch was a bottleneck and this is a ground up approach.
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