(6/n) We rely on PyTorch’s optimizer interface to design all our sparse algorithms as special optimizers, which operate on a sparse view of the model parameters and gradients during training. We use a wrapper over existing PyTorch optimizers, which enables efficient
PyTorch Sparse Optimizers for Efficient Model Training
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